Growing compact RBF networks using a genetic algorithm

Abstract

A novel approach for applying genetic algorithms to the configuration of radial basis function networks is presented. A new crossover operator that allows for some control over the competing conventions problem is introduced. Also, a minimalist initialization scheme which tends to generate more parsimonious models is also presented. Finally, a reformulation of generalized cross-validation criterion for model selection, making it more conservative, is discussed. The proposed model is submitted to a computational experiment in order to verify its effectiveness.