4.5 Article

An empirical study of impact of crossover operators on the performance of non-binary genetic algorithm based neural approaches for classification

期刊

COMPUTERS & OPERATIONS RESEARCH
卷 31, 期 4, 页码 481-498

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0305-0548(02)00229-0

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neural networks; discriminant analysis; genetic algorithms

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We study the performance of genetic algorithm (GA) based artificial neural network (ANN) for different crossover operators. We use simulated and real life data to test the performance of GA-based ANN. Our results indicate that arithmetic crossover operator may be a suitable crossover operator for GA based ANN.

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