Optimal Parameter for the Training of Multilayer Perceptron Neural Networks by Using Hierarchical Genetic Algorithm
Journal Article
·
· AIP Conference Proceedings
This paper deals with the controversial topic of the selection of the parameters of a genetic algorithm, in this case hierarchical, used for training of multilayer perceptron neural networks for the binary classification. The parameters to select are the crossover and mutation probabilities of the control and parametric genes and the permanency percent. The results can be considered as a guide for using this kind of algorithm.
- OSTI ID:
- 21251780
- Journal Information:
- AIP Conference Proceedings, Vol. 1060, Issue 1; Other Information: DOI: 10.1063/1.3037103; (c) 2008 American Institute of Physics; IeCCS 2007: International electronic conference on computer science, 28 June - 8 July 2007; Country of input: International Atomic Energy Agency (IAEA); ISSN 0094-243X
- Country of Publication:
- United States
- Language:
- English
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