Evolutionary Optimization of RBF Networks

One of the main obstacles to the widespread use of artijcial neural networks is the difJiculty of adequately define valuesfor their free parameters. This article discusses how Radial Basis Function, RBF; networks can have their parameters defined by genetic algorithms. For such, it presents an overall view of the problems involved and the different approaches used to genetically optimize RBF networks. Finally, a model is proposed which includes representation, crossover operator and multiobjective optimization criteria. Experimental results using this model are presented.

• Type: Conference
• Year: 2000
• Where: SBRN
• Authors: Estefane G. M. de Lacerda, Teresa Bernarda Ludermir, André Carlos Ponce Leon Ferreira de Carvalho
• Keywords: Artijcial Neural Networks, Neural Networks, Radial Basis Function, Rbf Networks, SBRN 2000