Combinatorial evolution of regression nodes in feedforward neural networks
暂无分享,去创建一个
[1] Avijit Saha,et al. Oriented Non-Radial Basis Functions for Image Coding and Analysis , 1990, NIPS.
[2] Michael Conrad,et al. Combining evolution with credit apportionment: A new learning algorithm for neural nets , 1994, Neural Networks.
[3] R. Storn,et al. Differential evolution a simple and efficient adaptive scheme for global optimization over continu , 1997 .
[4] Bernd Fritzke,et al. Growing cell structures--A self-organizing network for unsupervised and supervised learning , 1994, Neural Networks.
[5] David S. Broomhead,et al. Multivariable Functional Interpolation and Adaptive Networks , 1988, Complex Syst..
[6] Xin Yao,et al. A new evolutionary system for evolving artificial neural networks , 1997, IEEE Trans. Neural Networks.
[7] Rosalind W. Picard,et al. On the efficiency of the orthogonal least squares training method for radial basis function networks , 1996, IEEE Trans. Neural Networks.
[8] Stefan Bornholdt,et al. General asymmetric neural networks and structure design by genetic algorithms: a learning rule for temporal patterns , 1992, Proceedings of IEEE Systems Man and Cybernetics Conference - SMC.
[9] Kalyanmoy Deb,et al. An Investigation of Niche and Species Formation in Genetic Function Optimization , 1989, ICGA.
[10] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .
[11] John C. Platt. A Resource-Allocating Network for Function Interpolation , 1991, Neural Computation.
[12] Y Lu,et al. A Sequential Learning Scheme for Function Approximation Using Minimal Radial Basis Function Neural Networks , 1997, Neural Computation.
[13] J. Nadal,et al. Learning in feedforward layered networks: the tiling algorithm , 1989 .
[14] J. Saffery,et al. Using stereographic projection as a preprocessing technique for Upstart , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.
[15] Sheng Chen,et al. Practical identification of NARMAX models using radial basis functions , 1990 .
[16] L. Darrell Whitley,et al. Genetic algorithms and neural networks: optimizing connections and connectivity , 1990, Parallel Comput..
[17] Stephen A. Billings,et al. Radial basis function network configuration using genetic algorithms , 1995, Neural Networks.
[18] D. B. Fogel,et al. Using evolutionary programing to create neural networks that are capable of playing tic-tac-toe , 1993, IEEE International Conference on Neural Networks.
[19] Patrick K. Simpson,et al. Fuzzy min-max neural networks. I. Classification , 1992, IEEE Trans. Neural Networks.
[20] Shang-Liang Chen,et al. Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.
[21] John R. Koza,et al. Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.
[22] Hans-Michael Voigt,et al. Task Decomposition and Correlations in Growing Artificial Neural Networks , 1994 .
[23] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[24] E. Fiesler,et al. Comparative Bibliography of Ontogenic Neural Networks , 1994 .
[25] Peter J. B. Hancock,et al. Genetic algorithms and permutation problems: a comparison of recombination operators for neural net structure specification , 1992, [Proceedings] COGANN-92: International Workshop on Combinations of Genetic Algorithms and Neural Networks.
[26] Bruce A. Whitehead,et al. Evolving space-filling curves to distribute radial basis functions over an input space , 1994, IEEE Trans. Neural Networks.
[27] D. Broomhead,et al. Radial Basis Functions, Multi-Variable Functional Interpolation and Adaptive Networks , 1988 .
[28] Christian Lebiere,et al. The Cascade-Correlation Learning Architecture , 1989, NIPS.
[29] John E. Moody,et al. Fast Learning in Multi-Resolution Hierarchies , 1988, NIPS.
[30] Xin Yao,et al. A review of evolutionary artificial neural networks , 1993, Int. J. Intell. Syst..
[31] M. J. D. Powell,et al. Radial basis functions for multivariable interpolation: a review , 1987 .
[32] E. Littmann. Generalization Abilities of Cascade Network Architectures , 1992 .
[33] R. Scott Crowder,et al. Predicting the Mackey-Glass Timeseries With Cascade-Correlation Learning , 1990 .
[34] J. D. Schaffer,et al. Combinations of genetic algorithms and neural networks: a survey of the state of the art , 1992, [Proceedings] COGANN-92: International Workshop on Combinations of Genetic Algorithms and Neural Networks.
[35] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[36] J. Rissanen,et al. Modeling By Shortest Data Description* , 1978, Autom..
[37] P. Werbos,et al. Beyond Regression : "New Tools for Prediction and Analysis in the Behavioral Sciences , 1974 .
[38] Vittorio Maniezzo,et al. Genetic evolution of the topology and weight distribution of neural networks , 1994, IEEE Trans. Neural Networks.
[39] George A. F. Seber,et al. Linear regression analysis , 1977 .
[40] Tomas Hrycej. Modular learning in neural networks - a modularized approach to neural network classification , 1992, Sixth-Generation computer technology series.
[41] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .
[42] L. Glass,et al. Oscillation and chaos in physiological control systems. , 1977, Science.
[43] John Moody,et al. Fast Learning in Networks of Locally-Tuned Processing Units , 1989, Neural Computation.
[44] Bruce A. Whitehead,et al. Cooperative-competitive genetic evolution of radial basis function centers and widths for time series prediction , 1996, IEEE Trans. Neural Networks.
[45] Robert A. Jacobs,et al. Increased rates of convergence through learning rate adaptation , 1987, Neural Networks.
[46] Richard O. Duda,et al. Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.
[47] R. Palmer,et al. Introduction to the theory of neural computation , 1994, The advanced book program.
[48] Peter J. Angeline,et al. An evolutionary algorithm that constructs recurrent neural networks , 1994, IEEE Trans. Neural Networks.
[49] P. K. Simpson. Fuzzy Min-Max Neural Networks-Part 1 : Classification , 1992 .
[50] Dušan Petrovački,et al. Evolutional development of a multilevel neural network , 1993, Neural Networks.
[51] Hiroaki Kitano,et al. Designing Neural Networks Using Genetic Algorithms with Graph Generation System , 1990, Complex Syst..
[52] Wolfram Schiffmann,et al. Performance Evaluation of Evolutionarily Created Neural Network Topologies , 1990, PPSN.
[53] Helge Ritter,et al. Cascade network architectures , 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.
[54] David S. Watkins,et al. Fundamentals of matrix computations , 1991 .
[55] Robert W. Wilson,et al. Regressions by Leaps and Bounds , 2000, Technometrics.