Abstract
This paper presents a new evolutionary procedure to design optimal networks of Radial Basis Functions (RBFs). It defines a self-organizing process into a population of RBFs based on the estimation of the fitness for each neuron in the population, and on the use of operators that, according to a set of fuzzy rules, transform the RBFs. This way, it has been possible to define cooperation, speciation, and niching features in the evolution of the population. © Springer-Verlag Berlin Heidelberg 2003.
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CITATION STYLE
Rivera, A. J., Ortega, J., Rojas, I., & Del Jesús, M. J. (2003). Co-evolutionary algorithm for RBF by self-organizing population of neurons. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2686, 470–477. https://doi.org/10.1007/3-540-44868-3_60
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