We propose in this paper a novel prescriptive solution to decide the optimum number of neurons in the hidden-layer of multilayer feedforward neural networks. Our approach uses the unconstrained mixed integer nonlinear multicriteria optimization technique. We validate the algorithm using numerical ex
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A comparison of nonlinear optimization methods for supervised learning in multilayer feedforward neural networks
β Scribed by James W. Denton; Ming S. Hung
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 922 KB
- Volume
- 93
- Category
- Article
- ISSN
- 0377-2217
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