ABSTRACT Resumen En este artículo se presenta un nuevo elemento poblacional a considerar en el diseño de algoritmos evolutivos multiobjetivo para la optimización de Redes de Funciones de Base Radial. Concretamente, se divide la población en subpoblaciones virtuales, donde cada subpoblación está compuesta por individuos o redes con el mismo número de neuronas. El objetivo será mantener el mejor individuo (individuo élite) de cada subpoblación entre generaciones, consiguiendo aumentar la diversidad de la población. Este elemento se implementa en el algoritmo EMORBFN, ya presentado por los autores, y se aplica a la tarea de clasificación. En los resultados se puede observar cómo la introducción de este nuevo elemento mejora el comportamiento general del algoritmo. Palabras Clave: Diseño Multiobjetivo, Redes de Funciones de Base Radial, Elitismo.

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Available from: Antonio Jesús Rivera Rivas, Jun 26, 2014
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