## Abstract This paper describes the implementation of nonlinear optimization methods into the learning of neural networks (NN) and the speed efficiency of four proposed improvements into the backpropagation algorithm. The problems of the backpropagation learning method are pointed out first, and t
โฆ LIBER โฆ
Optimization of an artificial neural network for thermal/pressure food processing: Evaluation of training algorithms
โ Scribed by J.S. Torrecilla; L. Otero; P.D. Sanz
- Book ID
- 113551227
- Publisher
- Elsevier Science
- Year
- 2007
- Tongue
- English
- Weight
- 307 KB
- Volume
- 56
- Category
- Article
- ISSN
- 0168-1699
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Design optimization using approximations based on feed-forward back-propagation neural network is the topic of much recent research. The neural network schemes that have been proposed in the literature for optimal design of structural systems differ in their architecture and training procedures. Fur