P. N. Suganthan

发表

Neural-network-based system for recognition of partially occluded shapes and patterns

Dinesh P. Mital, Eam-Khwang Teoh, S. K. Amarasinghe, 1996, Other Conferences.

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..

Optimal Sizing and Placement of Distributed Generators and Capacitors in Radial Distribution Network

P. N. Suganthan, Partha Biswas, Gehan A. J. Amaratunga, 2017 .

Random Vector Functional Link Neural Network based Ensemble Deep Learning pdf

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

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.

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

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

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

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

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.

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

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

Optimization of Wind Turbine Rotor Diameters and Hub Heights in a Windfarm Using Differential Evolution Algorithm

P. N. Suganthan, Partha Biswas, Gehan A. J. Amaratunga, 2016, SocProS.

MMOGA for Solving Multimodal Multiobjective Optimization Problems with Local Pareto Sets

P. N. Suganthan, J. J. Liang, B. Y. Qu, 2020, 2020 IEEE Congress on Evolutionary Computation (CEC).

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

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

Random vector functional link neural network for short-term wind power ramp forecasting

P. N. Suganthan, Narasimalu Srikanth, Gehan A. J. Amaratunga, 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.

An Ensemble of Kernel Ridge Regression for Multi-class Classification

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

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 .

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.

Ensemble of niching algorithms

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

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

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

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).

Incremental Knowledge Tracing from Multiple Schools

P. N. Suganthan, Savitha Ramasamy, Cheryl Sze Yin Wong, 2022 .

Oblique and rotation double random forest pdf

P. N. Suganthan, M. Tanveer, V. Snasel, 2021, ArXiv.

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.

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

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

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

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

Design of Reconfigurable Antenna Array using Improved Multiagent Genetic Algorithms

P. N. Suganthan, S. Baskar, A. Alphones, 2004 .

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.

Robust growing neural gas algorithm with application in cluster analysis

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

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

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

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 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).

Empirical comparison of bagging-based ensemble classifiers

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

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.

Ensemble particle swarm optimizer

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

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

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

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.

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.

A comprehensive evaluation of random vector functional link networks

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

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

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

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..

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

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

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

P. N. Suganthan, G. Pugalenthi, R. Sowdhamini, 2007, BMC Bioinformatics.

Ensemble of Constraint Handling Techniques

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

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 .