Optimizing RBF Networks with Cooperative/Competitive Evolution of Units and Fuzzy Rules
作者： A. J. Rivera , J. Ortega , I. Rojas , A. Prieto
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摘要: This paper presents a new evolutionary method to design optimal networks of Radial Basis Functions (RBFs). The main characteristics this lie in the estimation fitness neurone population and choice operator apply; for latter objective, set fuzzy rules is used. Thus, considered here, done by considering three factors: weight neuron RBF Network, overlapping among neurons, distances from neurons points where approximation worst. These factors allow us define function which concepts such as cooperation, speciation, niching are taken into account. also used linguistic variables logic system choose apply. proposed has been tested with Mackey-Glass series.
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