2delta-gann: a New Approach to Training Neural Networks Using Genetic Algorithms
نویسندگان
چکیده
We describe a method of using Genetic Algorithms for training multi-layer perceptron neworks in which the chromosomes encode “rules” for changing the network weights rather than the weights themselves. The genetic operators of crossover, selection and mutation are used to generate new rules which are then applied to the weight matrix. The approach is significantly better than other approaches to training networks using genetic algorithms and successfully solves a number of benchmark problems which are known to be difficult for backward error propagation.
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