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  5. Training of radial basis networks by genetic algorithms with adaptive mutations

Training of radial basis networks by genetic algorithms with adaptive mutations

O.O. Bezsonov
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In this paper the efficiency of adaptive mutations in the genetic algorithms used for training radial basis network and optimisation of its structure is considered. We investigate the following types of adaptive mutations: decreasing Cauchy mutation, adaptive Gauss and Laplace mutations. A comparative analysis using simulation is conducted.
Keywords: neural network, genetic algorithm, adaptive mutation, basis function, selection, fitness function, chromosome, gene