Evolving RBF neural networks for time-series forecasting with EvRBF
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Juan Julián Merelo Guervós | Maribel García Arenas | Pedro Ángel Castillo Valdivieso | Víctor Manuel Rivas Santos | Francisco Javier García Castellano | J. J. M. Guervós | M. G. Arenas
[1] Zbigniew Michalewicz,et al. Genetic Algorithms + Data Structures = Evolution Programs , 1992, Artificial Intelligence.
[2] David White,et al. GANNet: A Genetic Algorithm for Optimizing Topology and Weights in Neural Network Design , 1993, IWANN.
[3] 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.
[4] Héctor Pomares,et al. Expert Mutation Operators for the Evolution of Radial Basis Function Neural Networks , 2001, IWANN.
[5] Bernd Fritzke. Supervised Learning with Growing Cell Structures , 1993, NIPS.
[6] Juan Julián Merelo Guervós,et al. G-Prop: Global optimization of multilayer perceptrons using GAs , 2000, Neurocomputing.
[7] Alaa F. Sheta,et al. Time-series forecasting using GA-tuned radial basis functions , 2001, Inf. Sci..
[8] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[9] Rudolf F. Albrecht,et al. Artificial Neural Nets and Genetic Algorithms , 1995, Springer Vienna.
[10] W. Light. Some Aspects of Radial Basis Function Approximation , 1992 .
[11] William H. Press,et al. The Art of Scientific Computing Second Edition , 1998 .
[12] B. C. Brookes,et al. Information Sciences , 2020, Cognitive Skills You Need for the 21st Century.
[13] CentresMark,et al. Regularisation in the Selection of Radial Basis Function , 1995 .
[14] Horst Bischof,et al. An efficient MDL-based construction of RBF networks , 1998, Neural Networks.
[15] Shang-Liang Chen,et al. Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.
[16] Juan Julián Merelo Guervós,et al. Evolving Multilayer Perceptrons , 2000, Neural Processing Letters.
[17] Friedhelm Schwenker,et al. Three learning phases for radial-basis-function networks , 2001, Neural Networks.
[18] Sheng Chen,et al. Regularized orthogonal least squares algorithm for constructing radial basis function networks , 1996 .
[19] Pedro A. Castillo,et al. Evolving RBF Neural Networks , 2001 .
[20] Mark J. L. Orr,et al. Regularization in the Selection of Radial Basis Function Centers , 1995, Neural Computation.
[21] Juan Julián Merelo Guervós,et al. G-lvq, a Combination of Genetic Algorithms and Lvq , 1995, ICANNGA.
[22] Christopher M. Bishop,et al. Current address: Microsoft Research, , 2022 .
[23] Zbigniew Michalewicz,et al. Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.
[24] John Moody,et al. Fast Learning in Networks of Locally-Tuned Processing Units , 1989, Neural Computation.
[25] D. Broomhead,et al. Radial Basis Functions, Multi-Variable Functional Interpolation and Adaptive Networks , 1988 .
[26] Panos A. Ligomenides,et al. GANNET: a genetic algorithm for searching topology and weight spaces in neural network design. The first step in finding a neural network solution , 1993 .
[27] Efstratios F. Georgopoulos,et al. Forecasting the MagnetoEncephaloGram (MEG) of Epileptic Patients Using Genetically Optimized Neural Networks , 1999, GECCO.
[28] Mark J. L. Orr. Optimising the widths of radial basis functions , 1998, Proceedings 5th Brazilian Symposium on Neural Networks (Cat. No.98EX209).
[29] William H. Press,et al. Numerical recipes in C , 2002 .
[30] Zbigniew Michalewicz,et al. Genetic Algorithms + Data Structures = Evolution Programs , 2000, Springer Berlin Heidelberg.
[31] John C. Platt. A Resource-Allocating Network for Function Interpolation , 1991, Neural Computation.
[32] Maarten Keijzer,et al. Evolving Objects: A General Purpose Evolutionary Computation Library , 2001, Artificial Evolution.