Evolutionary Algorithm Based Radial Basis Function Neural Network for Function Approximation

This study attempts to enhance the performance of radial basis function neural network (RBFnn) using self- organizing map neural network (SOMnn). In addition, the hybrid of genetic algorithm and particle swarm optimization (HGP) algorithm is employed to train RBFnn for function approximation. The proposed SOM-HGP evolutionary algorithm combines the automatically clustering ability of SOMnn and the HGP algorithm. Experimental results for three continuous test functions show that the algorithm has the best performance than GA (21), PSO (8), HPSGO (15) for training RBFnn.

[1]  Saeed Gholizadeh,et al.  Optimum design of structures by an improved genetic algorithm using neural networks , 2005, Adv. Eng. Softw..

[2]  Shang-Liang Chen,et al.  Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.

[3]  Minzhou Luo,et al.  Identification of Nonlinear System Based on a New Hybrid Gradient-Based PSO Algorithm , 2007, 2007 International Conference on Information Acquisition.

[4]  Chia-Feng Juang,et al.  Evolutionary fuzzy control of flexible AC transmission system , 2005 .

[5]  André da Motta Salles Barreto,et al.  GOLS - Genetic orthogonal least squares algorithm for training RBF networks , 2006, Neurocomputing.

[6]  Carl G. Looney,et al.  Advances in Feedforward Neural Networks: Demystifying Knowledge Acquiring Black Boxes , 1996, IEEE Trans. Knowl. Data Eng..

[7]  Patrick Siarry,et al.  Particle swarm and ant colony algorithms hybridized for improved continuous optimization , 2007, Appl. Math. Comput..

[8]  Zne-Jung Lee.  A novel hybrid algorithm for function approximation , 2008, Expert Syst. Appl..

[9]  Teuvo Kohonen,et al.  The self-organizing map , 1990 .

[10]  Gilbert Syswerda,et al.  Uniform Crossover in Genetic Algorithms , 1989, ICGA.

[11]  R. J. Kuo,et al.  Application of Radial Basis Function Neural Network for Sales Forecasting , 2009, 2009 International Asia Conference on Informatics in Control, Automation and Robotics.

[12]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[13]  Pankaj Singh,et al.  Suitability of different neural networks in daily flow forecasting , 2007, Appl. Soft Comput..

[14]  Donald C. Wunsch,et al.  Modeling of gene regulatory networks with hybrid differential evolution and particle swarm optimization , 2007, Neural Networks.

[15]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[16]  Hsuan-Ming Feng,et al.  Self-generation RBFNs using evolutional PSO learning , 2006, Neurocomputing.

[17]  D. E. Goldberg,et al.  Genetic Algorithms in Search, Optimization & Machine Learning , 1989 .

[18]  Haralambos Sarimveis,et al.  A new algorithm for developing dynamic radial basis function neural network models based on genetic algorithms , 2002, Comput. Chem. Eng..

[19]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[20]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[21]  Jose Miguel Puerta,et al.  Learning weighted linguistic fuzzy rules with estimation of distribution algorithms , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[22]  Aluizio F. R. Araújo,et al.  Identification and control of dynamical systems using the self-organizing map , 2004, IEEE Transactions on Neural Networks.

[23]  Chao-Ming Huang,et al.  An RBF Network With OLS and EPSO Algorithms for Real-Time Power Dispatch , 2007, IEEE Transactions on Power Systems.

[24]  Héctor Pomares,et al.  Soft-computing techniques and ARMA model for time series prediction , 2008, Neurocomputing.

[25]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[26]  Mohamad M. Awad,et al.  Multicomponent Image Segmentation Using a Genetic Algorithm and Artificial Neural Network , 2007, IEEE Geoscience and Remote Sensing Letters.