P. Suganthan

发表

Particle swarm optimiser with neighbourhood operator

P. Suganthan, 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

AFP-Pred: A random forest approach for predicting antifreeze proteins from sequence-derived properties.

P. Suganthan, T. Martinetz, K. Kandaswamy, 2011, Journal of theoretical biology.

Problem Definitions and Evaluation Criteria for the CEC 2010 Competition on Constrained Real- Parameter Optimization

P. Suganthan, R. Mallipeddi, 2010 .

Constrained multi-objective optimization algorithm with an ensemble of constraint handling methods

P. Suganthan, B. Qu, 2011 .

Dynamic multi-swarm particle swarm optimizer

Jing J. Liang, Ponnuthurai N. Suganthan, P. Suganthan, 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..

Swarm and Evolutionary Computing: Algorithms, Analyses, and Applications (IEEE Press Series on Computational Intelligence)

Ponnuthurai N. Suganthan, Swagatam Das, P. Suganthan, 2015 .

Differential evolution algorithm with ensemble of populations for global numerical optimization

P. Suganthan, R. Mallipeddi, 2009 .

Kernel neural gas algorithms with application to cluster analysis

A. K. Qin, P. Suganthan, 2004, ICPR 2004.

A hybrid tabu search algorithm with an efficient neighborhood structure for the flexible job shop scheduling problem

P. Suganthan, Jun-qing Li, Q. Pan, 2011 .

Multiple relational graphs mapping using genetic algorithms

K. G. Khoo, P. Suganthan, 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

Attributed relational graph matching by neural-gas networks

P. Suganthan, 2000, Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501).

SPRED: A machine learning approach for the identification of classical and non-classical secretory proteins in mammalian genomes.

P. Suganthan, T. Martinetz, K. Kandaswamy, 2010, Biochemical and biophysical research communications.

Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization

Jing J. Liang, P. N. Suganthan, Ponnuthurai Nagaratnam Suganthan, 2005 .

Identification of catalytic residues from protein structure using support vector machine with sequence and structural features.

P. Suganthan, G. Pugalenthi, K. Kumar, 2008, Biochemical and biophysical research communications.

Random Forests with ensemble of feature spaces

Ponnuthurai N. Suganthan, Le Zhang, P. Suganthan, 2014, Pattern Recognit..

SMpred: A Support Vector Machine Approach to Identify Structural Motifs in Protein Structure Without Using Evolutionary Information

P. Suganthan, T. Martinetz, K. Kandaswamy, 2010, Journal of biomolecular structure & dynamics.

A Multi-Populated Differential Evolution Algorithm for Solving Constrained Optimization Problem

Mehmet Fatih Tasgetiren, Ponnuthurai N. Suganthan, M. F. Tasgetiren, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Oblique Decision Tree Ensemble via Multisurface Proximal Support Vector Machine

Ponnuthurai N. Suganthan, Le Zhang, P. Suganthan, 2015, IEEE Transactions on Cybernetics.

A modified cultural algorithm with a balanced performance for the differential evolution frameworks

Robert G. Reynolds, Ponnuthurai N. Suganthan, Mostafa Z. Ali, 2016, Knowl. Based Syst..

A novel hybrid Cultural Algorithms framework with trajectory-based search for global numerical optimization

Robert G. Reynolds, Ponnuthurai N. Suganthan, Mostafa Z. Ali, 2016, Inf. Sci..

Bayesian optimization based dynamic ensemble for time series forecasting

P. Suganthan, Ruobin Gao, L. Du, 2022, Inf. Sci..

An Eecient Neural Gas Network for Classiication

P. Suganthan, 1998 .

Prediction of apoptosis protein locations with genetic algorithms and support vector machines through a new mode of pseudo amino acid composition.

Thomas Martinetz, Ganesan Pugalenthi, P N Suganthan, 2010, Protein and peptide letters.

A differential evolution algorithm for the no-idle flowshop scheduling problem with total tardiness criterion

M. F. Tasgetiren, P. Suganthan, Q. Pan, 2011 .

Stock Price Forecasting with Empirical Mode Decomposition Based Ensemble \nu -Support Vector Regression Model

G. Amaratunga, P. Suganthan, Xueheng Qiu, 2017, CICBA.

Kernel neural gas algorithms with application to cluster analysis

Matthieu Geist, Olivier Pietquin, Gabriel Fricout, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

Shape Indexing Using Relational Vectors and Neural Networks

P. Suganthan, Block, 2001 .

Evolutionary Multitask Optimization: Fundamental Research Questions, Practices, and Directions for the Future

J. Ser, E. Osaba, P. Suganthan, 2021, 2111.14463.

Differential evolution using improved crowding distance for multimodal multiobjective optimization

Jing J. Liang, Ponnuthurai N. Suganthan, Caitong Yue, 2021, Swarm Evol. Comput..

Tutorial 7—Adaptive Business Intelligence - Evolutionary Computation for Real World

Qingfu Zhang, Zbigniew Michalewicz, Riccardo Poli, 2007 .

Multiobjective Evolutionary Optimization

Ponnuthurai Nagaratnam Suganthan, Partha Biswas, P. Suganthan, 2018, Wiley Encyclopedia of Electrical and Electronics Engineering.

Problem Deflnitions and Evaluation Criteria for the CEC 2006 Special Session on Constrained Real-Parameter Optimization

Jing J. Liang, Carlos A. Coello Coello, Maurice Clerc, 2006 .

Introduction for Special Focus on Pigeon-Inspired Optimization

Ponnuthurai Nagaratnam Suganthan, Haibin Duan, Jing Liang, 2019, SCIENTIA SINICA Informationis.

Representation learning using deep random vector functional link networks for clustering

P. Suganthan, Minghui Hu, 2022, Pattern Recognit..

Nostradamus 2014: Prediction, Modeling and Analysis of Complex Systems

Ivan Zelinka, Ajith Abraham, Guanrong Chen, 2014 .

Pattern Classification Using Multiple SOMs

Nikhil R. Pal, Ponnuthurai N. Suganthan, P. Suganthan, 1998, ICONIP.

Mobile Node Dynamism using Particle Swarm Optimization to fight against Vulnerability Exploitations

A. K. Qin, P. Suganthan, Ying Tan, 2020 .

Ensemble deep learning: A review

M. A. Ganaie, P. Suganthan, Minghui Hu, 2021, Eng. Appl. Artif. Intell..

Jointly optimized ensemble deep random vector functional link network for semi-supervised classification

J. Ser, P. Suganthan, J. Del Ser, 2022, Eng. Appl. Artif. Intell..

A Hybrid Iterated Greedy Algorithm for a Crane Transportation Flexible Job Shop Problem

Quan-Ke Pan, Ponnuthurai Nagaratnam Suganthan, Junqing Li, 2022, IEEE Transactions on Automation Science and Engineering.

Oblique and rotation double random forest

M. A. Ganaie, P. Suganthan, V. Snášel, 2021, Neural Networks.

Automated layer-wise solution for ensemble deep randomized feed-forward neural network

P. Suganthan, Ruobin Gao, M. Tanveer, 2022, Neurocomputing.

An Enhanced Multi-Phase Stochastic Differential Evolution Framework for Numerical Optimization

P. Suganthan, Rami Alazrai, A. Awajan, 2022, 2022 IEEE Congress on Evolutionary Computation (CEC).

2019 IEEE Symposium Series on Computational Intelligence

Robert Kozma, Francisco Herrera, Raymond Chiong, 2019, IEEE Computational Intelligence Magazine.

Co-Trained Random Vector Functional Link Network

M. A. Ganaie, P. Suganthan, M. Tanveer, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

WITHDRAWN: Corrigendum to "Major Advances in Particle Swarm Optimization: Theory, Analysis, and Application" [Swarm and Evolutionary Computation 63 (2021) 1-40/100868]

Ponnuthurai N. Suganthan, Essam H. Houssein, Kashif Hussain, 2021, Swarm and Evolutionary Computation.

Prediction of functionally important sites from protein sequences using sparse kernel least squares classifiers.

P. Suganthan, G. Pugalenthi, S. Chakrabarti, 2009, Biochemical and biophysical research communications.

Significant wave height forecasting using hybrid ensemble deep randomized networks with neurons pruning

Kum Fai Yuen, P. Suganthan, Ruobin Gao, 2023, Eng. Appl. Artif. Intell..

Time Series Forecasting Using Online Performance-based Ensemble Deep Random Vector Functional Link Neural Network

P. Suganthan, Ruobin Gao, L. Du, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

Real-parameter unconstrained optimization based on enhanced fitness-adaptive differential evolution algorithm with novel mutation

P. Suganthan, A. W. Mohamed, 2017, Soft Computing.

Unified Discrete Diffusion for Simultaneous Vision-Language Generation

P. Suganthan, Heliang Zheng, Minghui Hu, 2022, ICLR.

Evolutionary Multitask Optimization: Fundamental research questions, practices, and directions for the future

J. Ser, E. Osaba, P. Suganthan, 2021, Swarm Evol. Comput..

A hybrid artificial bee colony algorithm for the job-shop scheduling problem with no-wait constraint

Chong Chin Soon, P. Suganthan, S. Sundar, 2015, Soft Computing.

Dynamic ensemble deep echo state network for significant wave height forecasting

Kum Fai Yuen, P. Suganthan, Minghui Hu, 2023, Applied Energy.

Takagi-Sugeno fuzzy based power system fault section diagnosis models via genetic learning adaptive GSK algorithm

P. Suganthan, Changsong Li, A. W. Mohamed, 2022, Knowl. Based Syst..

Trial-Based Dominance Enables Non-Parametric Tests to Compare both the Speed and Accuracy of Stochastic Optimizers

K. Price, P. Suganthan, Abhishek Kumar, 2022, ArXiv.

Graph ensemble deep random vector functional link network for traffic forecasting

P. Suganthan, Ruobin Gao, L. Du, 2022, Appl. Soft Comput..

Risk minimization in biometric sensor networks: an evolutionary multi-objective optimization approach

P. Suganthan, Swagatam Das, Soumyadip Sengupta, 2012, Soft Computing.

Multi-objective optimal power flow solutions using a constraint handling technique of evolutionary algorithms

P. Suganthan, R. Mallipeddi, P. Biswas, 2019, Soft Computing.

Experimental evaluation of stochastic configuration networks: Is SC algorithm inferior to hyper-parameter optimization method?

P. Suganthan, Minghui Hu, 2022, Appl. Soft Comput..

Minimum Variance Embedded Random Vector Functional Link Network with Privileged Information

Ponnuthurai N. Suganthan, M. Tanveer, M. A. Ganaie, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

Random vector functional link network: recent developments, applications, and future directions

M. A. Ganaie, Anil Kumar Malik, P. Suganthan, 2022, ArXiv.

A comprehensive evaluation of random vector functional link networks

P. N. Suganthan, Ponnuthurai N. Suganthan, Le Zhang, 2016, Inf. Sci..

Random vector functional link network for short-term electricity load demand forecasting

Ponnuthurai N. Suganthan, Narasimalu Srikanth, Gehan A. J. Amaratunga, 2016, Inf. Sci..

Bio-inspired computation: Where we stand and what's next

Xin-She Yang, Javier Del Ser, Francisco Herrera, 2019, Swarm Evol. Comput..

Recent advances in differential evolution - An updated survey

Ponnuthurai N. Suganthan, Sankha Subhra Mullick, Swagatam Das, 2016, Swarm Evol. Comput..

Ensemble Incremental Random Vector Functional Link Network for Short-term Crude Oil Price Forecasting

Ponnuthurai N. Suganthan, Xueheng Qiu, Gehan A. J. Amaratunga, 2018, 2018 IEEE Symposium Series on Computational Intelligence (SSCI).

Ensemble incremental learning Random Vector Functional Link network for short-term electric load forecasting

Ponnuthurai N. Suganthan, Xueheng Qiu, Gehan A. J. Amaratunga, 2018, Knowl. Based Syst..

Comprehensive evaluation of twin SVM based classifiers on UCI datasets

Ponnuthurai Nagaratnam Suganthan, Chandan Gautam, M. Tanveer, 2019, Appl. Soft Comput..

A Differential Covariance Matrix Adaptation Evolutionary Algorithm for real parameter optimization

Ponnuthurai N. Suganthan, Swagatam Das, Subhrajit Roy, 2012, Inf. Sci..

LisBON: A framework for parallelisation and hybridisation of optimisation algorithms

Ponnuthurai N. Suganthan, Tim Fühner, C. Dürr, 2007, 2007 IEEE Congress on Evolutionary Computation.

Feature Analysis and Classification of Protein Secondary Structure Data

Ponnuthurai N. Suganthan, Stanley Y. M. Shi, P. Suganthan, 2003, ICANN.

Swarm, Evolutionary, and Memetic Computing

Ponnuthurai Nagaratnam Suganthan, Suresh Chandra Satapathy, B. K. Panigrahi, 2013, Lecture Notes in Computer Science.

Comprehensive learning particle swarm optimizer for global optimization of multimodal functions

Jing J. Liang, A. Kai Qin, Ponnuthurai N. Suganthan, 2006, IEEE Transactions on Evolutionary Computation.

Dynamic multi-swarm particle swarm optimizer with harmony search

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2011, Expert Syst. Appl..

Leveraged Neighborhood Restructuring in Cultural Algorithms for Solving Real-World Numerical Optimization Problems

Robert G. Reynolds, Ponnuthurai N. Suganthan, Mostafa Z. Ali, 2016, IEEE Transactions on Evolutionary Computation.

Linear dimensionality reduction using relevance weighted LDA

Xin Yao, A. Kai Qin, Ponnuthurai N. Suganthan, 2005, Pattern Recognit..

Nonlinear Feature Extraction Using Evolutionary Algorithm

Xin Yao, Ponnuthurai N. Suganthan, E. Ke Tang, 2004, ICONIP.

Instance based random forest with rotated feature space

Ponnuthurai N. Suganthan, Le Zhang, Ye Ren, 2013, 2013 IEEE Symposium on Computational Intelligence and Ensemble Learning (CIEL).

Major Advances in Particle Swarm Optimization: Theory, Analysis, and Application

Ponnuthurai N. Suganthan, Essam H. Houssein, Kashif Hussain, 2021, Swarm Evol. Comput..

Evolutionary multiobjective optimization in dynamic environments: A set of novel benchmark functions

Ponnuthurai N. Suganthan, Swagatam Das, Carlos A. Coello Coello, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

Multiobjective evolutionary algorithms: A survey of the state of the art

Qingfu Zhang, Aimin Zhou, Ponnuthurai N. Suganthan, 2011, Swarm Evol. Comput..

Design of triangular FBG filter for sensor applications using covariance matrix adapted evolution algorithm

Ponnuthurai Nagaratnam Suganthan, Nam Quoc Ngo, Arokiaswami Alphones, 2006 .

Ensemble Classification and Regression-Recent Developments, Applications and Future Directions [Review Article]

Ponnuthurai N. Suganthan, Le Zhang, Ye Ren, 2016, IEEE Computational Intelligence Magazine.

Economic dispatch using hybrid grey wolf optimizer

T. Jayabarathi, Ponnuthurai Nagaratnam Suganthan, T. Raghunathan, 2016 .

Evolutionary extreme learning machine

A. Kai Qin, Ponnuthurai N. Suganthan, Guang-Bin Huang, 2005, Pattern Recognit..

Ensemble strategies for population-based optimization algorithms - A survey

Guohua Wu, Ponnuthurai N. Suganthan, Rammohan Mallipeddi, 2019, Swarm Evol. Comput..

Insights into Protein Sequence and Structure-Derived Features Mediating 3D Domain Swapping Mechanism using Support Vector Machine Based Approach

Ponnuthurai N. Suganthan, Ramanathan Sowdhamini, Khader Shameer, 2010, Bioinformatics and biology insights.

An Adaptive Differential Evolution Algorithm With Novel Mutation and Crossover Strategies for Global Numerical Optimization

Ponnuthurai N. Suganthan, Swagatam Das, Subhrajit Roy, 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Computational Intelligence in Sports

Iztok Fister, Ponnuthurai Nagaratnam Suganthan, Matjaž Perc, 2018, Adaptation, Learning, and Optimization.

Computational intelligence in sports: Challenges and opportunities within a new research domain

Matjaz Perc, Iztok Fister, Ponnuthurai N. Suganthan, 2015, Appl. Math. Comput..

Heterogeneous ensemble for power load demand forecasting

Ponnuthurai Nagaratnam Suganthan, Xueheng Qiu, Aruna Charukesi Palaninathan, 2016, 2016 IEEE Region 10 Conference (TENCON).

A Comparative Study of Empirical Mode Decomposition-Based Short-Term Wind Speed Forecasting Methods

P. N. Suganthan, Narasimalu Srikanth, Ye Ren, 2015, IEEE Transactions on Sustainable Energy.

Effective constructive and composite heuristics for grouping printed circuit boards in the electronic assembly industry

P. Suganthan, Q. Pan, Jiang-Ping Huang, 2021, Engineering Optimization.

Integration of functional information of genes in fuzzy clustering of short time series gene expression data

Nikhil R. Pal, Ponnuthurai N. Suganthan, Ashish Anand, 2010, IEEE Congress on Evolutionary Computation.

Solving dynamic economic emission dispatch problem considering wind power by multi-objective differential evolution with ensemble of selection method

Jing J. Liang, P. N. Suganthan, Y. S. Zhu, 2017, Natural Computing.

Ensemble strategies with adaptive evolutionary programming

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, S. Mallipeddi, 2010, Inf. Sci..

A survey on multi-objective evolutionary algorithms for the solution of the environmental/economic dispatch problems

Jing J. Liang, Ponnuthurai N. Suganthan, B. Y. Qu, 2018, Swarm Evol. Comput..

Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization

P. N. Suganthan, A. Kai Qin, Ponnuthurai N. Suganthan, 2009, IEEE Transactions on Evolutionary Computation.

Economic emission dispatch problems with stochastic wind power using summation based multi-objective evolutionary algorithm

Jing J. Liang, Z. Y. Wang, Ponnuthurai N. Suganthan, 2016, Inf. Sci..

Empirical comparison of bagging-based ensemble classifiers

P. N. Suganthan, Ponnuthurai N. Suganthan, Ren Ye, 2012, 2012 15th International Conference on Information Fusion.

Task Scheduling in Cloud Computing based on Meta-heuristics: Review, Taxonomy, Open Challenges, and Future Trends

Ponnuthurai N. Suganthan, Yaser Maher Wazery, Essam H. Houssein, 2021, Swarm Evol. Comput..

Enhanced neural gas network for prototype-based clustering

A. Kai Qin, Ponnuthurai N. Suganthan, A. K. Qin, 2005, Pattern Recognit..

Robust growing neural gas algorithm with application in cluster analysis

P. N. Suganthan, A. Kai Qin, Ponnuthurai N. Suganthan, 2004, Neural Networks.

Identification and analysis of transcription factor family-specific features derived from DNA and protein information

Ponnuthurai N. Suganthan, Gary B. Fogel, Ashish Anand, 2010, Pattern Recognit. Lett..

Prediction of Transcription Factor Families Using DNA Sequence Features

Ponnuthurai N. Suganthan, Gary B. Fogel, Ashish Anand, 2008, PRIB.

Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing

Ponnuthurai N. Suganthan, Swagatam Das, B. K. Panigrahi, 2012 .

A dynamic neighborhood learning based particle swarm optimizer for global numerical optimization

P. N. Suganthan, Ponnuthurai N. Suganthan, Swagatam Das, 2012, Inf. Sci..

Differential Evolution: A Survey of the State-of-the-Art

P. N. Suganthan, Swagatam Das, Ponnuthurai Nagaratnam Suganthan, 2011, IEEE Transactions on Evolutionary Computation.

Empirical Mode Decomposition based ensemble deep learning for load demand time series forecasting

Ponnuthurai Nagaratnam Suganthan, Xueheng Qiu, Gehan A. J. Amaratunga, 2017, Appl. Soft Comput..

Discrete harmony search algorithm for flexible job shop scheduling problem with multiple objectives

Quan-Ke Pan, Ponnuthurai N. Suganthan, Tay Jin Chua, 2016, J. Intell. Manuf..

Self-adaptive differential evolution with multi-trajectory search for large-scale optimization

Ponnuthurai N. Suganthan, Swagatam Das, Shi-Zheng Zhao, 2011, Soft Comput..

$I_{\rm SDE}$ +—An Indicator for Multi and Many-Objective Optimization

Ponnuthurai Nagaratnam Suganthan, Rammohan Mallipeddi, Trinadh Pamulapati, 2019, IEEE Transactions on Evolutionary Computation.

Dynamic Multi-Swarm Particle Swarm Optimization for Multi-objective optimization problems

Jing J. Liang, Ponnuthurai N. Suganthan, Bo-Yang Qu, 2012, 2012 IEEE Congress on Evolutionary Computation.

Improved MOCLPSO algorithm for environmental/economic dispatch

Ponnuthurai N. Suganthan, T. Aruldoss Albert Victoire, P. Suganthan, 2007, 2007 IEEE Congress on Evolutionary Computation.

Comprehensive learning particle swarm optimizer for solving multiobjective optimization problems

Jing J. Liang, Ponnuthurai N. Suganthan, Vicky Ling Huang, 2006, Int. J. Intell. Syst..

Oblique random forest ensemble via Least Square Estimation for time series forecasting

Ponnuthurai N. Suganthan, Le Zhang, Xueheng Qiu, 2017, Inf. Sci..

Video shot motion characterization based on hierarchical overlapped growing neural gas networks

Xiang Cao, P. N. Suganthan, Ponnuthurai N. Suganthan, 2003, Multimedia Systems.

An approach for classification of highly imbalanced data using weighting and undersampling

P. N. Suganthan, Gary B. Fogel, Ashish Anand, 2010, Amino Acids.

Artificial neural network regression as a local search heuristic for ensemble strategies in differential evolution

Iztok Fister, P. Suganthan, M. Perc, 2016 .

A test-suite of non-convex constrained optimization problems from the real-world and some baseline results

Guohua Wu, Abhishek Kumar, Swagatam Das, 2020, Swarm Evol. Comput..

Pattern recognition by homomorphic graph matching using Hopfield neural networks

Eam Khwang Teoh, Dinesh P. Mital, Ponnuthurai N. Suganthan, 1995, Image Vis. Comput..

A Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problems

Javier Del Ser, Ponnuthurai N. Suganthan, Carlos A. Coello Coello, 2021, Swarm Evol. Comput..

Metaheuristic algorithms for the quadratic assignment problem

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2013, 2013 IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS).

Performance assessment and exhaustive listing of 500+ nature inspired metaheuristic algorithms

P. Suganthan, Guohua Wu, Qizhang Luo, 2022, Swarm Evol. Comput..

DNA-Prot: Identification of DNA Binding Proteins from Protein Sequence Information using Random Forest

P. N. Suganthan, Ganesan Pugalenthi, P. Suganthan, 2009, Journal of biomolecular structure & dynamics.

Optimal power flow solutions using differential evolution algorithm integrated with effective constraint handling techniques

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, Gehan A. J. Amaratunga, 2018, Eng. Appl. Artif. Intell..

Optimal power flow solutions incorporating stochastic wind and solar power

Ponnuthurai Nagaratnam Suganthan, Partha Biswas, Gehan A. J. Amaratunga, 2017 .

Optimal reactive power dispatch with uncertainties in load demand and renewable energy sources adopting scenario-based approach

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, Gehan A. J. Amaratunga, 2019, Appl. Soft Comput..

Novel composition test functions for numerical global optimization

Jing J. Liang, Kalyanmoy Deb, Ponnuthurai N. Suganthan, 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..

Problem Definitions and Evaluation Criteria for CEC 2011 Competition on Testing Evolutionary Algorithms on Real World Optimization Problems

P. N. Suganthan, Swagatam Das, P. Suganthan, 2011 .

Multi-objective optimal power flow solutions using a constraint handling technique of evolutionary algorithms

P. N. Suganthan, Rammohan Mallipeddi, Partha Biswas, 2019, Soft Computing.

Multiobjective economic-environmental power dispatch with stochastic wind-solar-small hydro power

Ponnuthurai Nagaratnam Suganthan, Partha Biswas, Gehan A. J. Amaratunga, 2018 .

Ensemble of Constraint Handling Techniques for Single Objective Constrained Optimization

Swagatam Das, Ponnuthurai Nagaratnam Suganthan, Rammohan Mallipeddi, 2015 .

Efficient constraint handling for optimal reactive power dispatch problems

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, S. Baskar, 2012, Swarm Evol. Comput..

Multi objective evolutionary programming to solve environmental economic dispatch problem

Bijaya K. Panigrahi, Ponnuthurai N. Suganthan, B. K. Panigrahi, 2010, 2010 11th International Conference on Control Automation Robotics & Vision.

Ensemble of Constraint Handling Techniques

P. N. Suganthan, Ponnuthurai N. Suganthan, Rammohan Mallipeddi, 2010, IEEE Transactions on Evolutionary Computation.

Constrained multi-objective optimization algorithm with diversity enhanced differential evolution

Ponnuthurai N. Suganthan, Bo-Yang Qu, P. Suganthan, 2010, IEEE Congress on Evolutionary Computation.

An ensemble of differential evolution algorithms for constrained function optimization

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2010, IEEE Congress on Evolutionary Computation.

Crowding-based local differential evolution with speciation-based memory archive for dynamic multimodal optimization

Ponnuthurai N. Suganthan, Swagatam Das, Souvik Kundu, 2013, GECCO '13.

Niching particle swarm optimization with local search for multi-modal optimization

Jing J. Liang, Ponnuthurai N. Suganthan, Bo-Yang Qu, 2012, Inf. Sci..

Ensemble of Clearing Differential Evolution for Multi-modal Optimization

Jing J. Liang, Ponnuthurai N. Suganthan, Bo-Yang Qu, 2012, ICSI.

Memetic Fitness Euclidean-Distance Particle Swarm Optimization for Multi-modal Optimization

Jing J. Liang, Ponnuthurai N. Suganthan, Bo-Yang Qu, 2011, ICIC.

Real-parameter evolutionary multimodal optimization - A survey of the state-of-the-art

Ponnuthurai N. Suganthan, Swagatam Das, Bo-Yang Qu, 2011, Swarm Evol. Comput..

Dynamic Grouping Crowding Differential Evolution with Ensemble of Parameters for Multi-modal Optimization

Ponnuthurai N. Suganthan, Bo-Yang Qu, Pushpan Gouthanan, 2010, SEMCCO.

Modified species-based differential evolution with self-adaptive radius for multi-modal optimization

P. N. Suganthan, P. Suganthan, B. Qu, 2010, International Conference on Computational Problem-Solving.

Current position-based Fitness Euclidean-distance Ratio Particle Swarm Optimizer for multi-modal optimization

Ponnuthurai N. Suganthan, Bo-Yang Qu, Shi-Zheng Zhao, 2010, 2010 Second World Congress on Nature and Biologically Inspired Computing (NaBIC).

Novel multimodal problems and differential evolution with ensemble of restricted tournament selection

Ponnuthurai N. Suganthan, Bo-Yang Qu, P. Suganthan, 2010, IEEE Congress on Evolutionary Computation.

Empirical comparison of niching methods on hybrid composition functions

Ponnuthurai N. Suganthan, Ling Yu, P. Suganthan, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Multi-objective harmony search algorithm for layout design in theatre hall acoustics

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai Nagaratnam Suganthan, 2015 .

A local-best harmony search algorithm with dynamic sub-harmony memories for lot-streaming flow shop scheduling problem

Jing J. Liang, Mehmet Fatih Tasgetiren, Quan-Ke Pan, 2011, Expert Syst. Appl..

Dynamic multi-swarm particle swarm optimizer with sub-regional harmony search

Ponnuthurai N. Suganthan, Swagatam Das, Shi-Zheng Zhao, 2010, IEEE Congress on Evolutionary Computation.

Solving lot-streaming flow shop scheduling problems using a discrete harmony search algorithm

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2010, IEEE Congress on Evolutionary Computation.

A self-adaptive global best harmony search algorithm for continuous optimization problems

Jing J. Liang, Mehmet Fatih Tasgetiren, Quan-Ke Pan, 2010, Appl. Math. Comput..

A local-best harmony search algorithm with dynamic subpopulations

Quan-Ke Pan, Ponnuthurai Nagaratnam Suganthan, Jing Liang, 2010 .

A Harmony Search Algorithm with Ensemble of Parameter Sets

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2009, 2009 IEEE Congress on Evolutionary Computation.

Differential evolution with multi-population based ensemble of mutation strategies

Guohua Wu, Ponnuthurai N. Suganthan, Huangke Chen, 2016, Inf. Sci..

Differential evolution algorithm with ensemble of parameters and mutation strategies

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2011, Appl. Soft Comput..

A multiobjective approach for optimal placement and sizing of distributed generators and capacitors in distribution network

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, Gehan A. J. Amaratunga, 2017, Appl. Soft Comput..

An improved differential evolution algorithm using efficient adapted surrogate model for numerical optimization

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, Mostafa Z. Ali, 2018, Inf. Sci..

Ensemble sinusoidal differential covariance matrix adaptation with Euclidean neighborhood for solving CEC2017 benchmark problems

Ponnuthurai N. Suganthan, Mostafa Z. Ali, Noor H. Awad, 2017, 2017 IEEE Congress on Evolutionary Computation (CEC).

Problem Definitions and Evaluation Criteria for the CEC 2014 Special Session and Competition on Single Objective Real-Parameter Numerical Optimization

Ponnuthurai Nagaratnam Suganthan, Jing Liang, Boyang Qu, 2014 .

A variable reduction strategy for evolutionary algorithms handling equality constraints

Witold Pedrycz, Guohua Wu, Ponnuthurai N. Suganthan, 2015, Appl. Soft Comput..

Heterogeneous comprehensive learning particle swarm optimization with enhanced exploration and exploitation

Ponnuthurai N. Suganthan, Nandar Lynn, P. Suganthan, 2015, Swarm Evol. Comput..

Multi-population differential evolution with balanced ensemble of mutation strategies for large-scale global optimization

P. N. Suganthan, Ponnuthurai N. Suganthan, Mostafa Z. Ali, 2015, Appl. Soft Comput..

Multiobjective optimization Test Instances for the CEC 2009 Special Session and Competition

Qingfu Zhang, Aimin Zhou, Ponnuthurai Nagaratnam Suganthan, 2009 .

An ensemble sinusoidal parameter adaptation incorporated with L-SHADE for solving CEC2014 benchmark problems

Robert G. Reynolds, Ponnuthurai N. Suganthan, Mostafa Z. Ali, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

An improved class of real-coded Genetic Algorithms for numerical optimization✰

Robert G. Reynolds, P. N. Suganthan, Ponnuthurai N. Suganthan, 2018, Neurocomputing.

A Novel Empirical Mode Decomposition With Support Vector Regression for Wind Speed Forecasting

Ponnuthurai N. Suganthan, Narasimalu Srikanth, Ye Ren, 2016, IEEE Transactions on Neural Networks and Learning Systems.

Large-Scale Portfolio Optimization Using Multiobjective Evolutionary Algorithms and Preselection Methods

Ponnuthurai Nagaratnam Suganthan, P. Suganthan, B. Qu, 2017 .

Two-lbests based multi-objective particle swarm optimizer

Ponnuthurai Nagaratnam Suganthan, Shi-Zheng Zhao, P. Suganthan, 2011 .

Multi-objective optimization using self-adaptive differential evolution algorithm

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, Vicky Ling Huang, 2009, 2009 IEEE Congress on Evolutionary Computation.

Multi-objective optimization based on self-adaptive differential evolution algorithm

Mehmet Fatih Tasgetiren, A. Kai Qin, Ponnuthurai N. Suganthan, 2007, 2007 IEEE Congress on Evolutionary Computation.

Multiobjective Differential Evolution with External Archive and Harmonic Distance-Based Diversity Measure

P. N. Suganthan, S. Baskar, A. K. Qin, 2007 .

Comparison between MOEA/D and NSGA-III on a set of novel many and multi-objective benchmark problems with challenging difficulties

Qingfu Zhang, Kalyanmoy Deb, Lei Chen, 2019, Swarm Evol. Comput..

Problem Definitions for Performance Assessment of Multi-objective Optimization Algorithms

Jing J. Liang, Mike Preuss, Eckart Zitzler, 2007 .

A Benchmark-Suite of real-World constrained multi-objective optimization problems and some baseline results

Ponnuthurai Nagaratnam Suganthan, Rammohan Mallipeddi, Swagatam Das, 2021, Swarm Evol. Comput..

Real-parameter constrained optimization using enhanced quality-based cultural algorithm with novel influence and selection schemes

Ponnuthurai N. Suganthan, Mohammad I. Daoud, Rami Alazrai, 2021, Inf. Sci..

Using variable reduction strategy to accelerate evolutionary optimization

Witold Pedrycz, Haifeng Li, Guohua Wu, 2017, Appl. Soft Comput..

Differential evolution with ensemble of constraint handling techniques for solving CEC 2010 benchmark problems

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, P. Suganthan, 2010, IEEE Congress on Evolutionary Computation.

Diversity enhanced Adaptive Evolutionary Programming for solving single objective constrained problems

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, Bo-Yang Qu, 2009, 2009 IEEE Congress on Evolutionary Computation.

Dynamic Multi-Swarm Particle Swarm Optimizer with a Novel Constraint-Handling Mechanism

Jing J. Liang, Ponnuthurai N. Suganthan, P. Suganthan, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Self-adaptive Differential Evolution Algorithm for Constrained Real-Parameter Optimization

A. Kai Qin, Ponnuthurai N. Suganthan, Vicky Ling Huang, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Solving the steelmaking casting problem using an effective fruit fly optimisation algorithm

Quan-Ke Pan, Kun Mao, Ponnuthurai N. Suganthan, 2014, Knowl. Based Syst..

Computing with the collective intelligence of honey bees - A survey

Ponnuthurai N. Suganthan, Swagatam Das, Anguluri Rajasekhar, 2017, Swarm Evol. Comput..

Optimal placement and sizing of FACTS devices for optimal power flow in a wind power integrated electrical network

P. N. Suganthan, B. K. Panigrahi, Rammohan Mallipeddi, 2020, Neural Computing and Applications.

Deep and machine learning techniques for medical imaging-based breast cancer: A comprehensive review

Abdelmgeid A. Ali, Ponnuthurai N. Suganthan, Essam H. Houssein, 2021, Expert Syst. Appl..

A survey of randomized algorithms for training neural networks

Le Zhang, Ponnuthurai N. Suganthan, P. Suganthan, 2016, Inf. Sci..

Real-parameter unconstrained optimization based on enhanced fitness-adaptive differential evolution algorithm with novel mutation

Ali Wagdy Mohamed, Ponnuthurai N. Suganthan, P. Suganthan, 2017, Soft Computing.

Design of Yagi-Uda antennas using comprehensive learning particle swarm optimisation

Jing J. Liang, Ponnuthurai Nagaratnam Suganthan, Arokiaswami Alphones, 2005 .

Self-adaptive differential evolution algorithm for numerical optimization

A. Kai Qin, Ponnuthurai N. Suganthan, A. K. Qin, 2005, 2005 IEEE Congress on Evolutionary Computation.

Analyzing convergence performance of evolutionary algorithms: A statistical approach

Francisco Herrera, Salvador García, Ponnuthurai N. Suganthan, 2014, Inf. Sci..

Solving Traffic Signal Scheduling Problems in Heterogeneous Traffic Network by Using Meta-Heuristics

MengChu Zhou, Rong Su, Ponnuthurai Nagaratnam Suganthan, 2019, IEEE Transactions on Intelligent Transportation Systems.

Meta-Heuristics for Bi-Objective Urban Traffic Light Scheduling Problems

Rong Su, Ponnuthurai Nagaratnam Suganthan, Kaizhou Gao, 2019, IEEE Transactions on Intelligent Transportation Systems.

A hybrid artificial bee colony algorithm for the job-shop scheduling problem with no-wait constraint

Ponnuthurai N. Suganthan, Shyam Sundar, Tay Jin Chua, 2015, Soft Computing.

An improved artificial bee colony algorithm for flexible job-shop scheduling problem with fuzzy processing time

Quan-Ke Pan, Ponnuthurai N. Suganthan, Tay Jin Chua, 2016, Expert Syst. Appl..

A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion

Quan-Ke Pan, Ponnuthurai N. Suganthan, Tay Jin Chua, 2015, Expert Syst. Appl..

Modified Artificial Bee Colony Algorithm with Comprehensive Learning Re-initialization Strategy

Ponnuthurai N. Suganthan, Nandar Lynn, P. Suganthan, 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

A Swarm Intelligence Approach to Flexible Job-Shop Scheduling Problem with No-Wait Constraint in Remanufacturing

Ponnuthurai N. Suganthan, Tay Jin Chua, Shyam Sundar, 2013, ICAISC.

A discrete artificial bee colony algorithm for the no-idle permutation flowshop scheduling problem with the total tardiness criterion

Quan-Ke Pan, Ponnuthurai Nagaratnam Suganthan, M. Fatih Tasgetiren, 2013 .

Migrating forager population in a multi-population Artificial Bee Colony algorithm with modified perturbation schemes

Bijaya K. Panigrahi, Ponnuthurai N. Suganthan, Swagatam Das, 2013, 2013 IEEE Symposium on Swarm Intelligence (SIS).

A discrete artificial bee colony algorithm for the total flowtime minimization in permutation flow shops

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2011, Inf. Sci..

A discrete artificial bee colony algorithm for the lot-streaming flow shop scheduling problem

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2011, Inf. Sci..

A discrete artificial bee colony algorithm for the permutation flow shop scheduling problem with total flowtime criterion

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2010, IEEE Congress on Evolutionary Computation.

Ensemble particle swarm optimizer

P. N. Suganthan, Ponnuthurai N. Suganthan, Nandar Lynn, 2017, Appl. Soft Comput..

CADE: A hybridization of Cultural Algorithm and Differential Evolution for numerical optimization

Robert G. Reynolds, Ponnuthurai N. Suganthan, Mostafa Z. Ali, 2017, Inf. Sci..

A Differential Evolution Approach for Robust Adaptive Beamforming Based on Joint Estimation of Look Direction and Array Geometry

Ponnuthurai Nagaratnam Suganthan, Sirajudeen Gulam Razul, Chong Meng Samson See, 2011 .

Benchmark Generator for CEC'2009 Competition on Dynamic Optimization

Xin Yao, Changhe Li, Shengxiang Yang, 2008 .

An Adaptive Resource Allocation Strategy for Objective Space Partition-Based Multiobjective Optimization

Witold Pedrycz, Xiaomin Zhu, Guohua Wu, 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Constrained real parameter optimization with a gradient repair based Differential Evolution algorithm

Ponnuthurai N. Suganthan, Swagatam Das, Sayan Maity, 2011, 2011 IEEE Symposium on Differential Evolution (SDE).

LINEAR ANTENNA ARRAY SYNTHESIS WITH CONSTRAINED MULTI-OBJECTIVE DIFFERENTIAL EVOLUTION

Swagatam Das, Ponnuthurai Nagaratnam Suganthan, Boyang Qu, 2010, Progress In Electromagnetics Research B.

Synthesis and Design of Thinned Planar Concentric Circular Antenna Array - A Multi-objective Approach

Ponnuthurai N. Suganthan, Swagatam Das, Subhrajit Roy, 2011, SEMCCO.

Non-uniform Circular-Shaped Antenna Array Design and Synthesis - A Multi-Objective Approach

Ponnuthurai N. Suganthan, Swagatam Das, Subhrajit Roy, 2011, SEMCCO.

Multi-objective evolutionary programming without non-domination sorting is up to twenty times faster

Ponnuthurai N. Suganthan, Bo-Yang Qu, P. Suganthan, 2009, 2009 IEEE Congress on Evolutionary Computation.

Diversity enhanced particle swarm optimizer for global optimization of multimodal problems

Ponnuthurai N. Suganthan, Shuguang Zhao, P. Suganthan, 2009, 2009 IEEE Congress on Evolutionary Computation.

Ensemble Reinforcement Learning: A Survey

P. Suganthan, W. Pedrycz, Junwei Ou, 2023, ArXiv.

Robust Visual Tracking Using Oblique Random Forests

Narendra Ahuja, Le Zhang, Ponnuthurai N. Suganthan, 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Design of Non-Uniform Circular Antenna Arrays Using a Modified Invasive Weed Optimization Algorithm

Swagatam Das, Prithwish Chakraborty, Gourab Ghosh Roy, 2011, IEEE Transactions on Antennas and Propagation.

SVMCRYS: an SVM approach for the prediction of protein crystallization propensity from protein sequence.

Ganesan Pugalenthi, P N Suganthan, Krishna Kumar Kandaswamy, 2010, Protein and peptide letters.

An iterative cyclic tri-strategy hybrid stochastic fractal with adaptive differential algorithm for global numerical optimization

P. Suganthan, A. Awajan, Mostafa Z. Ali, 2023, Inf. Sci..

Novel benchmark functions for continuous multimodal optimization with comparative results

Jing J. Liang, Z. Y. Wang, Ponnuthurai N. Suganthan, 2016, Swarm Evol. Comput..

Benchmark Functions for the CEC'2013 Special Session and Competition on Large-Scale Global Optimization

Ponnuthurai Nagaratnam Suganthan, Ke Tang, Xin Yao, 2008 .

Ensemble of differential evolution variants

Haifeng Li, Guohua Wu, Anping Lin, 2018, Inf. Sci..

Random Vector Functional Link Neural Network based Ensemble Deep Learning pdf

P. N. Suganthan, M. Tanveer, Rakesh Katuwal, 2019, ArXiv.

Time series classification using diversified Ensemble Deep Random Vector Functional Link and Resnet features

Ponnuthurai N. Suganthan, Rakesh Katuwal, Wen Xin Cheng, 2021, Appl. Soft Comput..

Oblique Random Forests on Residual Network Features

Wen Xin Cheng, Ponnuthurai N. Suganthan, Rakesh Katuwal, 2020, ICONIP.

Ensemble of niching algorithms

P. N. Suganthan, E. L. Yu, P. Suganthan, 2010, Inf. Sci..

Solving manpower scheduling problem in manufacturing using mixed-integer programming with a two-stage heuristic algorithm

Quan-Ke Pan, Ponnuthurai Nagaratnam Suganthan, Tay J. Chua, 2010 .

Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling

Quan-Ke Pan, Ponnuthurai N. Suganthan, Tay Jin Chua, 2014, Inf. Sci..

Multi-Class Protein Fold Recognition Using Multi-Objective Evolutionary Algorithms

Kalyanmoy Deb, Ponnuthurai Nagaratnam Suganthan, Stanley Y. M. Shi, 2004 .

Multi-objective evolutionary algorithms based on the summation of normalized objectives and diversified selection

Ponnuthurai N. Suganthan, Bo-Yang Qu, P. Suganthan, 2010, Inf. Sci..

Evolutionary programming with ensemble of explicit memories for dynamic optimization

Ponnuthurai N. Suganthan, Ling Yu, P. Suganthan, 2009, 2009 IEEE Congress on Evolutionary Computation.

Evaluation of novel adaptive evolutionary programming on four constraint handling techniques

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, P. Suganthan, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Dynamic multi-swarm particle swarm optimizer with local search

Jing J. Liang, Ponnuthurai N. Suganthan, P. Suganthan, 2005, 2005 IEEE Congress on Evolutionary Computation.

Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2016, Knowl. Based Syst..

Withdrawal notice to: ' WITHDRAWN: Major Advances in Particle Swarm Optimization: Theory, Analysis, and Application' Swarm and Evolutionary Computation 63 (2021) 1-40/100868'

Ponnuthurai N. Suganthan, Essam H. Houssein, Kashif Hussain, 2021, Swarm and Evolutionary Computation.

Situation Awareness Recognition Using EEG and Eye-Tracking data: a pilot study

P. Suganthan, O. Sourina, Ruobin Gao, 2022, 2022 International Conference on Cyberworlds (CW).

Effective ensembles of heuristics for scheduling flexible job shop problem with new job insertion

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2015, Comput. Ind. Eng..

Ensemble Deep Random Vector Functional Link Neural Network for Regression

P. Suganthan, Minghui Hu, Rakesh Katuwal, 2023, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Weighting and pruning based ensemble deep random vector functional link network for tabular data classification

Ponnuthurai Nagaratnam Suganthan, Rakesh Katuwal, Qiushi Shi, 2022, Pattern Recognit..

Alzheimer's Disease Diagnosis via Intuitionistic Fuzzy Random Vector Functional Link Network

M. A. Ganaie, Anil Kumar Malik, P. Suganthan, 2022, IEEE Transactions on Computational Social Systems.

On the origins of randomization-based feedforward neural networks

Ponnuthurai N. Suganthan, Rakesh Katuwal, P. Suganthan, 2021, Appl. Soft Comput..

Benchmarking Optimization-Based Energy Disaggregation Algorithms

Oladayo S. Ajani, Swagatam Das, P. Suganthan, 2022, Energies.

Evolutionary Multitask Optimization: Are we Moving in the Right Direction?

Javier Del Ser, Ponnuthurai N. Suganthan, Eneko Osaba, 2021, ArXiv.

Ensemble deep learning for regression and time series forecasting

Le Zhang, Xueheng Qiu, Gehan Amaratunga, 2014, 2014 IEEE Symposium on Computational Intelligence in Ensemble Learning (CIEL).

Stacked Autoencoder Based Deep Random Vector Functional Link Neural Network for Classification

P. Suganthan, Rakesh Katuwal, 2019, Appl. Soft Comput..

General twin support vector machine with pinball loss function

Ponnuthurai N. Suganthan, Muhammad Tanveer, A. Sharma, 2019, Inf. Sci..

Identification of functionally diverse lipocalin proteins from sequence information using support vector machine

P. N. Suganthan, Ganesan Pugalenthi, Krishna Kumar Kandaswamy, 2010, Amino Acids.

Ensemble deep learning: A review pdf

Ponnuthurai N. Suganthan, M. Tanveer, M. A. Ganaie, 2021, Engineering applications of artificial intelligence.

Random vector functional link network: recent developments, applications, and future directions

M. A. Ganaie, Anil Kumar Malik, P. Suganthan, 2022, Appl. Soft Comput..

Echo state neural network based ensemble deep learning for short-term load forecasting

Kum Fai Yuen, P. Suganthan, Ruobin Gao, 2022, 2022 IEEE Symposium Series on Computational Intelligence (SSCI).

A Novel Ensemble Method of RVFL For Classification Problem

Ponnuthurai N. Suganthan, M. A. Ganaie, Muhammad Tanveer, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Ensemble methods for wind and solar power forecasting—A state-of-the-art review

Ponnuthurai Nagaratnam Suganthan, Narasimalu Srikanth, Ye Ren, 2015 .

A survey on meta-heuristics for solving disassembly line balancing, planning and scheduling problems in remanufacturing

Ponnuthurai Nagaratnam Suganthan, Kaizhou Gao, Z. M. He, 2020, Swarm Evol. Comput..

Versatile LiDAR-Inertial Odometry With SE(2) Constraints for Ground Vehicles

P. Suganthan, Minghui Hu, Han Wang, 2023, IEEE Robotics and Automation Letters.

A novel concurrent particle swarm optimization

Ponnuthurai N. Suganthan, S. Baskar, P. Suganthan, 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

Population topologies for particle swarm optimization and differential evolution

Ponnuthurai N. Suganthan, Mostafa Z. Ali, Nandar Lynn, 2017, Swarm Evol. Comput..

A novel hybrid discrete differential evolution algorithm for blocking flow shop scheduling problems

Ponnuthurai N. Suganthan, Quan-Ke Pan, Ling Wang, 2010, Comput. Oper. Res..

Robust visual tracking via co-trained Kernelized correlation filters

Le Zhang, Ponnuthurai N. Suganthan, P. Suganthan, 2017, Pattern Recognit..

Multi-Modal and Multi-User Semantic Communications for Channel-Level Information Fusion

Qing Guo, P. Suganthan, Ruobin Gao, 2022, IEEE Wireless Communications.

Synthetic Datasets for Numeric Uncertainty Quantification: Proposing Datasets for Future Researchers

Shady M. K. Mohamed, D. Srinivasan, P. Suganthan, 2023, IEEE Systems, Man, and Cybernetics Magazine.

A differential evolution algorithm with self-adapting strategy and control parameters

Liang Gao, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2011, Comput. Oper. Res..

Differential Evolution Algorithm with Ensemble of Parameters and Mutation and Crossover Strategies

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, P. Suganthan, 2010, SEMCCO.

Pattern recognition by graph matching using the Potts MFT neural networks

Eam Khwang Teoh, Dinesh P. Mital, Ponnuthurai N. Suganthan, 1995, Pattern Recognit..

Dynamic multi-swarm particle swarm optimizer with local search for Large Scale Global Optimization

Jing J. Liang, Mehmet Fatih Tasgetiren, Ponnuthurai N. Suganthan, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Structural pattern recognition using genetic algorithms

Ponnuthurai N. Suganthan, P. Suganthan, 2002, Pattern Recognit..

An ensemble of discrete differential evolution algorithms for solving the generalized traveling salesman problem

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2010, Appl. Math. Comput..

A Distance-Based Locally Informed Particle Swarm Model for Multimodal Optimization

Ponnuthurai N. Suganthan, Swagatam Das, Bo-Yang Qu, 2013, IEEE Transactions on Evolutionary Computation.

Metaheuristics for Common Due Date Total Earliness and Tardiness Single Machine Scheduling Problem

Quan-Ke Pan, Ponnuthurai Nagaratnam Suganthan, Yun-Chia Liang, 2009 .

Differential Evolution Algorithms for the Generalized Assignment problem

Mehmet Fatih Tasgetiren, Ponnuthurai N. Suganthan, Tay Jin Chua, 2009, 2009 IEEE Congress on Evolutionary Computation.

A Discrete Differential Evolution Algorithm for the No-Wait Flowshop Scheduling Problem with Total Flowtime Criterion

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2007, 2007 IEEE Symposium on Computational Intelligence in Scheduling.

Very high-resolution satellite image segmentation using variable-length multi-objective genetic clustering for multi-class change detection

P. Suganthan, S. Mukhopadhyay, D. Chakraborty, 2022, J. King Saud Univ. Comput. Inf. Sci..

Chaotic Heterogeneous Comprehensive Learning Particle Swarm Optimizer Variants for Permanent Magnet Synchronous Motor Models Parameters Estimation

Ponnuthurai Nagaratnam Suganthan, Dalia Yousri, M. B. Eteiba, 2020 .

An analysis of diversity measures

Xin Yao, Ponnuthurai N. Suganthan, E. Ke Tang, 2006, Machine Learning.

On Attributed Relational Graph Matching Using Hopfield Network

Eam Khwang Teoh, Dinesh P. Mital, Ponnuthurai N. Suganthan, 1994, European Conference on Artificial Intelligence.

Efficient Feature Extraction Based on Regularized Uncorrelated Chernoff Discriminant Analysis

A. Kai Qin, Ponnuthurai N. Suganthan, Marco Loog, 2006, 18th International Conference on Pattern Recognition (ICPR'06).

An efficient Differential Evolution algorithm for stochastic OPF based active-reactive power dispatch problem considering renewable generators

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, Mostafa Z. Ali, 2019, Appl. Soft Comput..

Ensemble of parameters in a sinusoidal differential evolution with niching-based population reduction

Ponnuthurai N. Suganthan, Mostafa Z. Ali, Noor H. Awad, 2017, Swarm Evol. Comput..

Modeling of steelmaking process with effective machine learning techniques

Ponnuthurai N. Suganthan, Ren Ye, Dipak Laha, 2015, Expert Syst. Appl..

Flexible Job-Shop Rescheduling for New Job Insertion by Using Discrete Jaya Algorithm

MengChu Zhou, Ponnuthurai Nagaratnam Suganthan, Kaizhou Gao, 2019, IEEE Transactions on Cybernetics.

Iterated greedy algorithms for the blocking flowshop scheduling problem with makespan criterion

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Damla Kizilay, 2017, Comput. Oper. Res..

Effective heuristics for the no-wait flow shop scheduling problem with total flow time minimization

Quan-Ke Pan, Ponnuthurai Nagaratnam Suganthan, Junqing Li, 2013 .

An improved iterated greedy algorithm for the distributed assembly permutation flowshop scheduling problem

Ponnuthurai Nagaratnam Suganthan, Liang Gao, Quan-Ke Pan, 2020, Comput. Ind. Eng..

A Greedy Cooperative Co-Evolutionary Algorithm With Problem-Specific Knowledge for Multiobjective Flowshop Group Scheduling Problems

Liang Gao, Quan-Ke Pan, Ponnuthurai Nagaratnam Suganthan, 2021, IEEE Transactions on Evolutionary Computation.

Ensemble Many-Objective Optimization Algorithm Based on Voting Mechanism

Witold Pedrycz, Ponnuthurai Nagaratnam Suganthan, Jianghan Zhu, 2022, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Decomposition-Based Multiobjective Evolutionary Algorithm With an Ensemble of Neighborhood Sizes

Qingfu Zhang, Ponnuthurai N. Suganthan, Shi-Zheng Zhao, 2012, IEEE Transactions on Evolutionary Computation.

Differential Evolution With Neighborhood Mutation for Multimodal Optimization

Jing J. Liang, Ponnuthurai N. Suganthan, Bo-Yang Qu, 2012, IEEE Transactions on Evolutionary Computation.

Artificial neural network regression as a local search heuristic for ensemble strategies in differential evolution

Iztok Fister, Ponnuthurai Nagaratnam Suganthan, Damjan Strnad, 2015, Nonlinear Dynamics.

Unit commitment - a survey and comparison of conventional and nature inspired algorithms

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, P. Suganthan, 2014, Int. J. Bio Inspired Comput..

A variable iterated greedy algorithm with differential evolution for the no-idle permutation flowshop scheduling problem

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2013, Comput. Oper. Res..

An Adaptive Multipopulation Differential Evolution With Dynamic Population Reduction

Robert G. Reynolds, Ponnuthurai Nagaratnam Suganthan, Mostafa Z. Ali, 2017, IEEE Transactions on Cybernetics.

Statistical analysis of convergence performance throughout the evolutionary search: A case study with SaDE-MMTS and Sa-EPSDE-MMTS

Francisco Herrera, Salvador García, Ponnuthurai N. Suganthan, 2013, 2013 IEEE Symposium on Differential Evolution (SDE).

Problem Definitions and Evaluation Criteria for CEC 2015 Special Session on Bound Constrained Single-Objective Computationally Expensive Numerical Optimization

Ponnuthurai Nagaratnam Suganthan, B. Y. Qu, J. J. Liang, 2015 .

Design of Fractional Order Controller for a servohydraulic positioning system with micro Artificial Bee Colony algorithm

P. N. Suganthan, Swagatam Das, Anguluri Rajasekhar, 2012, 2012 IEEE Congress on Evolutionary Computation.

Empirical Mode Decomposition-k Nearest Neighbor Models for Wind Speed Forecasting

P. N. Suganthan, Ye Ren, P. Suganthan, 2014 .

Parameter estimation of solar cells using datasheet information with the application of an adaptive differential evolution algorithm

Ponnuthurai Nagaratnam Suganthan, Partha Biswas, Gehan A. J. Amaratunga, 2019, Renewable Energy.

Static and dynamic photovoltaic models’ parameters identification using Chaotic Heterogeneous Comprehensive Learning Particle Swarm Optimizer variants

Ponnuthurai Nagaratnam Suganthan, Dalia Yousri, M. B. Eteiba, 2019, Energy Conversion and Management.

Cluster-based differential evolution with heterogeneous influence for numerical optimization

Jafar Albadarneh, Rehab Duwairi, Noor H. Awad, 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

Multiclass cancer classification by support vector machines with class-wise optimized genes and probability estimates.

Ashish Anand, P N Suganthan, P. Suganthan, 2009, Journal of theoretical biology.

A Voting-Mechanism-Based Ensemble Framework for Constraint Handling Techniques

P. Suganthan, W. Pedrycz, Guohua Wu, 2022, IEEE Transactions on Evolutionary Computation.

An ensemble approach with external archive for multi- and many-objective optimization with adaptive mating mechanism and two-level environmental selection

Ponnuthurai Nagaratnam Suganthan, Rammohan Mallipeddi, Vikas Palakonda, 2021, Inf. Sci..

A balanced fuzzy Cultural Algorithm with a modified Levy flight search for real parameter optimization

Robert G. Reynolds, Ponnuthurai N. Suganthan, Mostafa Z. Ali, 2018, Inf. Sci..

Differential evolution with orthogonal array-based initialization and a novel selection strategy

Ponnuthurai N. Suganthan, Partha P. Biswas, Abhishek Kumar, 2021, Swarm Evol. Comput..

Evolutionary many-Objective algorithm based on fractional dominance relation and improved objective space decomposition strategy

Guohua Wu, Ponnuthurai Nagaratnam Suganthan, Jianghan Zhu, 2021, Swarm Evol. Comput..

A hybrid ARIMA-DENFIS method for wind speed forecasting

Ponnuthurai N. Suganthan, Narasimalu Srikanth, Ren Ye, 2013, 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Proceedings of the Fifth International Conference on Fuzzy and Neuro Computing (FANCCO - 2015)

Swagatam Das, Ponnuthurai Nagaratnam Suganthan, B. K. Panigrahi, 2015, Advances in Intelligent Systems and Computing.

Solving system-level synthesis problem by a multi-objective estimation of distribution algorithm

Min Liu, Ling Wang, Ponnuthurai N. Suganthan, 2014, Expert Syst. Appl..

A Hybrid Algorithm for Urban LULC Change Detection for Building Smart-city by Using WorldView Images

P. Suganthan, D. Chakraborty, Ramen Pal, 2023, Journal of the Institution of Electronics and Telecommunication Engineers.

Regularized robust fuzzy least squares twin support vector machine for class imbalance learning

P. N. Suganthan, M. Tanveer, M. A. Ganaie, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Recognition of handprinted Chinese characters by constrained graph matching

Hong Yan, Ponnuthurai N. Suganthan, P. Suganthan, 1998, Image Vis. Comput..

Optimal encoding of graph homomorphism energy using fuzzy information aggregation operators

Hong Yan, Eam Khwang Teoh, Dinesh P. Mital, 1998, Pattern Recognit..

Optimal mapping of graph homomorphism onto self organising Hopfield network

Eam Khwang Teoh, Dinesh P. Mital, Ponnuthurai N. Suganthan, 1997, Image Vis. Comput..

Walk-forward empirical wavelet random vector functional link for time series forecasting

Ponnuthurai N. Suganthan, Kum Fai Yuen, Ruobin Gao, 2021, Appl. Soft Comput..

Ensemble for Solving Quadratic Assignment Problems

Ponnuthurai N. Suganthan, Meng-Hiot Lim, Li Qin Song, 2009, 2009 International Conference of Soft Computing and Pattern Recognition.

Ensemble of classification models with weighted functional link network

Ponnuthurai N. Suganthan, M. A. Ganaie, Mohammad Tanveer, 2021, Appl. Soft Comput..

Least squares KNN-based weighted multiclass twin SVM

Ponnuthurai Nagaratnam Suganthan, Muhammad Tanveer, A. Sharma, 2020, Neurocomputing.

Oblique Decision Tree Ensemble via Twin Bounded SVM

Ponnuthurai Nagaratnam Suganthan, M. A. Ganaie, M. Tanveer, 2020, Expert Syst. Appl..

An Ensemble of Kernel Ridge Regression for Multi-class Classification

P. N. Suganthan, Katuwal Rakesh, P. Suganthan, 2017, ICCS.

Evolutionary Computation for Theatre Hall Acoustics

Mehmet Fatih Tasgetiren, Ponnuthurai N. Suganthan, Ayca Kirimtat, 2018, Optimization in Industry.

ROBUST ADAPTIVE BEAMFORMING BASED ON COVARIANCE MATRIX RECONSTRUCTION FOR LOOK DIRECTION MISMATCH

Ponnuthurai Nagaratnam Suganthan, Sirajudeen Gulam Razul, Rammohan Mallipeddi, 2011 .

Minimizing harmonic distortion in power system with optimal design of hybrid active power filter using differential evolution

Ponnuthurai N. Suganthan, Gehan A. J. Amaratunga, Partha P. Biswas, 2017, Appl. Soft Comput..

Multiclass protein fold recognition using multiobjective evolutionary algorithms

Kalyanmoy Deb, Ponnuthurai N. Suganthan, Stanley Y. M. Shi, 2004, 2004 Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Particle swarm optimization algorithms with novel learning strategies

Jing J. Liang, A. Kai Qin, Ponnuthurai N. Suganthan, 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

Letter: On non-iterative learning algorithms with closed-form solution

Ponnuthurai N. Suganthan, P. Suganthan, 2018, Appl. Soft Comput..

Short-term wind power ramp forecasting with empirical mode decomposition based ensemble learning techniques

Ponnuthurai N. Suganthan, Xueheng Qiu, Gehan A. J. Amaratunga, 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI).

Visual Tracking With Convolutional Random Vector Functional Link Network

Le Zhang, Ponnuthurai Nagaratnam Suganthan, P. Suganthan, 2017, IEEE Transactions on Cybernetics.

An ensemble of decision trees with random vector functional link networks for multi-class classification

Le Zhang, Ponnuthurai N. Suganthan, Rakesh Katuwal, 2017, Appl. Soft Comput..

Performance Evaluation of Multiagent Genetic Algorithm

Jing J. Liang, A. Kai Qin, Ponnuthurai N. Suganthan, 2006, Natural Computing.

Benchmark Functions for the CEC'2010 Special Session and Competition on Large-Scale

Xiaodong Li, Zhenyu Yang, Ponnuthurai Nagaratnam Suganthan, 2009 .

A Reinforcement Learning-assisted Genetic Programming Algorithm for Team Formation Problem Considering Person-Job Matching

P. Suganthan, W. Pedrycz, Lei He, 2023, ArXiv.

Benchmarking Ensemble Classifiers with Novel Co-Trained Kernal Ridge Regression and Random Vector Functional Link Ensembles [Research Frontier]

P. N. Suganthan, Le Zhang, Ponnuthurai N. Suganthan, 2017, IEEE Computational Intelligence Magazine.

Multi-objective differential evolution with diversity enhancement

Ponnuthurai N. Suganthan, Bo-Yang Qu, P. Suganthan, 2010, Journal of Zhejiang University SCIENCE C.

Tool wear prediction using long short-term memory variants and hybrid feature selection techniques

P. Suganthan, K. Kotecha, Shylendra Kumar, 2022, The International Journal of Advanced Manufacturing Technology.

Comprehensive learning particle swarm optimizer for solving multiobjective optimization problems: Research Articles

Ponnuthurai Nagaratnam Suganthan, V. L. Huang, J. J. Liang, 2006 .

Multi-objective robust PID controller tuning using two lbests multi-objective particle swarm optimization

Ponnuthurai N. Suganthan, S. Baskar, M. Willjuice Iruthayarajan, 2011, Inf. Sci..

Predicting protein structural class by SVM with class-wise optimized features and decision probabilities.

Ganesan Pugalenthi, Ashish Anand, P N Suganthan, 2008, Journal of theoretical biology.

A machine learning approach for the identification of odorant binding proteins from sequence-derived properties

Ponnuthurai N. Suganthan, Ramanathan Sowdhamini, Ganesan Pugalenthi, 2007, BMC Bioinformatics.

Empirical mode decomposition based adaboost-backpropagation neural network method for wind speed forecasting

Ponnuthurai N. Suganthan, Xueheng Qiu, Ye Ren, 2014, 2014 IEEE Symposium on Computational Intelligence in Ensemble Learning (CIEL).

An improved brain storm optimisation algorithm for energy-efficient train operation problem

Jing J. Liang, Ponnuthurai N. Suganthan, Caitong Yue, 2021, Int. J. Bio Inspired Comput..

Hierarchical overlapped growing neural gas networks with applications to video shot detection and motion characterization

P. N. Suganthan, Ponnuthurai Nagaratnam Suganthan, Xiang Cao, 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

A comprehensive review of the deep learning-based tumor analysis approaches in histopathological images: segmentation, classification and multi-learning tasks

P. Suganthan, A. Awajan, Mostafa Z. Ali, 2023, Cluster Computing.

IF2Net: Innately Forgetting-Free Networks for Continual Learning

P. Suganthan, Kenji Kawaguchi, Zhigang Zeng, 2023, arXiv.org.

Online Continual Learning for Control of Mobile Robots

P. Suganthan, Savitha Ramasamy, Andriy Sarabakha, 2023, 2023 International Joint Conference on Neural Networks (IJCNN).

Class-Incremental Learning on Multivariate Time Series Via Shape-Aligned Temporal Distillation

P. Suganthan, Xudong Jiang, R. Savitha, 2023, IEEE International Conference on Acoustics, Speech, and Signal Processing.

Unsupervised Generative Variational Continual Learning

P. Suganthan, Savitha Ramasamy, C. Wong, 2022, 2022 IEEE International Conference on Image Processing (ICIP).

Comprehensive learning particle swarm optimizer for global optimization of multimodal functions

Jing J. Liang, P. N. Suganthan, A. K. Qin, 2006, IEEE Transactions on Evolutionary Computation.

SFE: A Simple, Fast, and Efficient Feature Selection Algorithm for High-Dimensional Data

P. Suganthan, A. Khosravi, M. Menhaj, 2023, IEEE Transactions on Evolutionary Computation.

Random vector functional link neural network based ensemble deep learning for short-term load forecasting

Kum Fai Yuen, P. Suganthan, Ruobin Gao, 2021, Expert Syst. Appl..

Design and modeling of adaptive IIR filtering systems using a weighted sum - variable length particle swarm optimization

Ponnuthurai N. Suganthan, Seyed Hamid Zahiri, Seyyed Mohammad Razavi, 2021, Appl. Soft Comput..

Chaotic Heterogeneous Comprehensive Learning Particle Swarm Optimizer Variants for Permanent Magnet Synchronous Motor Models Parameters Estimation

P. Suganthan, M. Eteiba, Dalia Allam, 2019, Iranian Journal of Science and Technology, Transactions of Electrical Engineering.

Unit commitment using time-ahead priority list and heterogeneous comprehensive learning PSO

Ponnuthurai N. Suganthan, Rammohan Mallipeddi, Nandar Lynn, 2019, 2019 IEEE Symposium Series on Computational Intelligence (SSCI).

Comprehensive learning particle swarm optimizer with guidance vector selection

Ponnuthurai N. Suganthan, Nandar Lynn, P. Suganthan, 2013, 2013 IEEE Symposium on Swarm Intelligence (SIS).

Mobile Node Dynamism using Particle Swarm Optimization to fight against Vulnerability Exploitations

P. N. Suganthan, Wang Wei-ping, Kun Liu, 2012 .

Optimal Multi-objective Reactive Power Dispatch Considering Static Voltage Stability Based on Dynamic Multi-group Self-Adaptive Differential Evolution Algorithm

P. N. Suganthan, Weirong Chen, Xuexia Zhang, 2012, 2012 Second International Conference on Intelligent System Design and Engineering Application.

Adaptive Comprehensive Learning Particle Swarm Optimizer with History Learning

Jing J. Liang, Ponnuthurai N. Suganthan, P. Suganthan, 2006, SEAL.

Evaluation of Comprehensive Learning Particle Swarm Optimizer

Jing J. Liang, A. Kai Qin, Ponnuthurai N. Suganthan, 2004, ICONIP.

Differential evolution with stochastic fractal search algorithm for global numerical optimization

Ponnuthurai N. Suganthan, Edward Jaser, Mostafa Z. Ali, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Neural Network Based Temporal Video Segmentation

Xiang Cao, Ponnuthurai N. Suganthan, P. Suganthan, 2002, Int. J. Neural Syst..

Task-Agnostic Continual Learning Using Base-Child Classifiers

Ponnuthurai Nagaratnam Suganthan, Savitha Ramasamy, Saisubramaniam Gopalakrishnan, 2021, 2021 IEEE International Conference on Image Processing (ICIP).

A decremental stochastic fractal differential evolution for global numerical optimization

Ponnuthurai N. Suganthan, Edward Jaser, Mostafa Z. Ali, 2016, Inf. Sci..

Shallow Neural Networks to Deep Neural Networks for Probabilistic Wind Forecasting

B. K. Panigrahi, P. Suganthan, Parul Arora, 2021, 2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS).

Visual Tracking with Convolutional Neural Network

Ponnuthurai N. Suganthan, Le Zhang, P. Suganthan, 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

Collaborative Truck-Drone Routing for Contactless Parcel Delivery During the Epidemic

P. Suganthan, Guohua Wu, Qizhang Luo, 2022, IEEE Transactions on Intelligent Transportation Systems.

Hybrid Multi-Objective Optimization Approach With Pareto Local Search for Collaborative Truck-Drone Routing Problems Considering Flexible Time Windows

P. Suganthan, Guohua Wu, Qizhang Luo, 2022, IEEE Transactions on Intelligent Transportation Systems.

Heterogeneous oblique random forest

Ponnuthurai N. Suganthan, Rakesh Katuwal, Le Zhang, 2020, Pattern Recognit..

A kernel-ensemble bagging support vector machine

P. N. Suganthan, Ponnuthurai N. Suganthan, Ren Ye, 2012, 2012 12th International Conference on Intelligent Systems Design and Applications (ISDA).

A Novel Support Vector Machine Approach to High Entropy Data Fragment Classification

Ponnuthurai N. Suganthan, Vrizlynn L. L. Thing, Qiming Li, 2010, SAISMC.

Enhancing Multi-Class Classification of Random Forest using Random Vector Functional Neural Network and Oblique Decision Surfaces

Ponnuthurai N. Suganthan, Rakesh Katuwal, P. Suganthan, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Extended Features Based Random Vector Functional Link Network for Classification Problem

M. A. Ganaie, P. Suganthan, A. K. Malik, 2022, IEEE Transactions on Computational Social Systems.

Voting-mechanism based ensemble constraint handling technique for real-world single-objective constrained optimization

Rui Wang, Guohua Wu, Ponnuthurai Nagaratnam Suganthan, 2020, 2020 IEEE Congress on Evolutionary Computation (CEC).

Initialization insensitive LVQ algorithm based on cost-function adaptation

A. Kai Qin, Ponnuthurai N. Suganthan, A. K. Qin, 2005, Pattern Recognit..

Large Initial Population and Neighborhood Search incorporated in LSHADE to solve CEC2020 Benchmark Problems

Ponnuthurai N. Suganthan, Partha P. Biswas, P. Suganthan, 2020, 2020 IEEE Congress on Evolutionary Computation (CEC).

Opposition-mutual learning differential evolution with hybrid mutation strategy for large-scale economic load dispatch problems with valve-point effects and multi-fuel options

P. Suganthan, A. W. Mohamed, Guojiang Xiong, 2022, Information Sciences.

Feature Selection for Microarray Data Using Least Squares SVM and Particle Swarm Optimization

Xin Yao, Ponnuthurai N. Suganthan, E. Ke Tang, 2005, 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

A cultural evolution with a modified selection function and adaptive α-cognition procedure for numerical optimization

R. Reynolds, P. Suganthan, Mostafa Z. Ali, 2023, Appl. Soft Comput..

A hybrid cuckoo search algorithm in parallel batch processing machines with unequal job ready times

Ponnuthurai N. Suganthan, Arindam Majumder, Dipak Laha, 2018, Comput. Ind. Eng..

Problem feature based meta-heuristics with Q-learning for solving urban traffic light scheduling problems

P. Suganthan, Kaizhou Gao, Z. Lin, 2023, Applied Soft Computing.

A novel dependency-oriented mixed-attribute data classification method

P. Suganthan, J. Huang, Yulin He, 2022, Expert Syst. Appl..

Random vector functional link neural network based ensemble deep learning

P. Suganthan, M. Tanveer, Qiushi Shi, 2021, Pattern Recognit..

Bilevel Optimization Using Bacteria Foraging Optimization Algorithm

Ponnuthurai N. Suganthan, Soumya Banerjee, Gautam Mahapatra, 2014, SEMCCO.

Decomposition-Based Multiobjective Evolutionary Algorithm With an Ensemble of Neighborhood Sizes

P. Suganthan, Qingfu Zhang, Shi-Zheng Zhao, 2012, IEEE Transactions on Evolutionary Computation.

Optimal Power Flow Solutions Using Algorithm Success History Based Adaptive Differential Evolution with Linear Population Reduction

Ponnuthurai N. Suganthan, Gehan A. J. Amaratunga, Partha P. Biswas, 2018, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Towards generating random forests via extremely randomized trees

Ponnuthurai N. Suganthan, Le Zhang, Ye Ren, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Ensemble and Arithmetic Recombination-Based Speciation Differential Evolution for Multimodal Optimization

Ponnuthurai N. Suganthan, Sheldon Hui, P. Suganthan, 2016, IEEE Transactions on Cybernetics.

Enhanced Direct Linear Discriminant Analysis for Feature Extraction on High Dimensional Data

A. Kai Qin, Ponnuthurai N. Suganthan, Marco Loog, 2005, AAAI.

Gene selection algorithms for microarray data based on least squares support vector machine

Xin Yao, Ponnuthurai N. Suganthan, E. Ke Tang, 2006, BMC Bioinformatics.

Fusion of multiple indicators with ensemble incremental learning techniques for stock price forecasting

Ponnuthurai Nagaratnam Suganthan, Xueheng Qiu, Gehan A. J. Amaratunga, 2019, Journal of Banking and Financial Technology.

Constrained self-adaptive differential evolution based design of robust optimal fixed structure controller

P. N. Suganthan, S. Baskar, S. Sivananaithaperumal, 2011, Eng. Appl. Artif. Intell..

Dynamic economic emission dispatch based on multi-objective pigeon-inspired optimization with double disturbance

Li Yan, Ponnuthurai Nagaratnam Suganthan, Yongsheng Zhu, 2019, Science China Information Sciences.

Genetic‐algorithm‐based design of a reconfigurable antenna array with discrete phase shifters

Ponnuthurai Nagaratnam Suganthan, Arokiaswami Alphones, S. Baskar, 2005 .

A Differential Evolution Framework with Ensemble of Parameters and Strategies and Pool of Local Search Algorithms

Ponnuthurai N. Suganthan, Giovanni Iacca, Fabio Caraffini, 2014, EvoApplications.

Identification of structurally conserved residues of proteins in absence of structural homologs using neural network ensemble

Ponnuthurai N. Suganthan, Ganesan Pugalenthi, E. Ke Tang, 2008, Bioinform..

Video Sequence Boundary Detection Using Neural Gas Networks

Xiang Cao, Ponnuthurai N. Suganthan, P. Suganthan, 2001, ICANN.

Upper bounds on Taillard’s benchmark suite for the no-wait flowshop scheduling problem with makespan criterion

Mehmet Fatih Tasgetiren, Quan-Ke Pan, Ponnuthurai N. Suganthan, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Combining classifiers based on confidence values

Ponnuthurai N. Suganthan, Ajantha S. Atukorale, P. Suganthan, 1999, Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318).

Ensemble Reinforcement Learning: A Survey

P. Suganthan, W. Pedrycz, Junwei Ou, 2023, Applied Soft Computing.

Objective function decomposition within genetic algorithm

K. G. Khoo, P. Suganthan, 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

A novel kernel prototype-based learning algorithm

A. Kai Qin, Ponnuthurai N. Suganthan, A. K. Qin, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

Effective heuristics for the no-wait flow shop scheduling problem with total flow time minimization

P. Suganthan, Jun-qing Li, K. Gao, 2012, The International Journal of Advanced Manufacturing Technology.

A composite heuristic for the no-wait flow shop scheduling

Ponnuthurai N. Suganthan, Zhen-Qiang Bao, Kai-Zhou Gao, 2012, 2012 IEEE Congress on Evolutionary Computation.

Discrete harmony search algorithm for flexible job shop scheduling problem with multiple objectives

P. Suganthan, Q. Pan, T. Chua, 2014, Journal of Intelligent Manufacturing.

Pareto-based discrete harmony search algorithm for flexible job shop scheduling

Ponnuthurai N. Suganthan, Tay Jin Chua, Kai-Zhou Gao, 2012, 2012 12th International Conference on Intelligent Systems Design and Applications (ISDA).

Ensembles of Double Random Forest

M. A. Ganaie, P. Suganthan, M. Tanveer, 2021 .

Genetic Algorithm for Silhouette Matching

Ponnuthurai N. Suganthan, Y. Li, Y. J. Wang, 2006, 2006 9th International Conference on Control, Automation, Robotics and Vision.

Multiobjective Particle Swarm optimizer with dynamic epsilon-dominance sorting

Ponnuthurai N. Suganthan, Bo-Yang Qu, Shi-Zheng Zhao, 2010, 2010 Second World Congress on Nature and Biologically Inspired Computing (NaBIC).

Large-scale data classification based on the integrated fusion of fuzzy learning and graph neural network

P. Suganthan, Ruobin Gao, Lingping Kong, 2023, Inf. Fusion.

Inpatient Discharges Forecasting for Singapore Hospitals by Machine Learning

Kum Fai Yuen, P. Suganthan, Ruobin Gao, 2022, IEEE Journal of Biomedical and Health Informatics.

Constraint Handling in Transmission Network Expansion Planning

Bijaya K. Panigrahi, Ponnuthurai N. Suganthan, Ashu Verma, 2010, SEMCCO.

Probabilistic Wind Power Forecasting Using Optimized Deep Auto-Regressive Recurrent Neural Networks

P. Suganthan, A. Khosravi, S. Ahmadian, 2023, IEEE Transactions on Industrial Informatics.

Problem Definitions and Evaluation Criteria for the CEC 2014 Special Session and Competition on Single Objective Real-Parameter Numerical Optimization

P. Suganthan, B. Qu, Jing-Chang Liang, 2014 .