Application of ANOVA to a cooperative-coevolutionary optimization of RBFNs

Authors:
Antonio J. Rivera;Ignacio Rojas;Julio Ortega
Affiliations:
Departamento de Informática, Universidad de Jaén;Departamento de Arquitectura y Tecnología de Computadores, Universidad de Granada;Departamento de Arquitectura y Tecnología de Computadores, Universidad de Granada
Venue:
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Year:
2005

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Abstract

In this paper the behaviour of a multiobjective cooperative-coevolutive hybrid algorithm for the optimization of the parameters defining a Radial Basis Function Network developed by our group, is analyzed. In order to demonstrate the robustness of the behaviour of the presented methodology when the parameters of the algorithm are modified, a statistical analysis has been carried out. In the present contribution, the relevance and relative importance of the parameters involved in the design of the multiobjective cooperative-coevolutive hybrid algorithm presented are investigated by using a powerful statistical tool, the ANalysis Of the VAriance (ANOVA). To demonstrate the robustness of our algorithm, a functional approximation problem is investigated.