Function mapping strategy in nonlinear optimization using neural networks
學年 83
學期 1
發表日期 1994-12-15
作品名稱 Function mapping strategy in nonlinear optimization using neural networks
作品名稱（其他語言）
著者 Shih, C. J.;Yang, T. L.
作品所屬單位 淡江大學機械與機電工程學系
出版者
會議名稱 1994 International Symposium on Artificial Neural Networks
會議地點 臺南, 臺灣
摘要 This paper proposes a zero-order method of nonlinear optimization using back-propagation nets, refer to as neural network nonlinear programming, or NNNLP. The primary procedure includes (1) training of a network to represent an explicit or implicit objective function, (2) examination of the feasibility of mapping function, (3) addition of training sets, (4) reduction of design space, (5) retraining of a mapping network, and (6) searching of an optimum solution. NNNLP works like a parallel multi-line search instead of one-line search in traditional optimization methods. This strategy increases the possibility of obtaining a global optimal solution and provides a totally new perspective of solving an optimization problem. Several constrained and unconstrained problems are solved by this approach and compared with the existing method. The accuracy and efficiency of this method can be improved by enhancing the computer capability and neural network architecture.
關鍵字 類神經網路;非線性最佳化;映對函數;Neural Network;Nonlinear Optimization;Mapping Function
語言 en
收錄於
會議性質 國際
校內研討會地點
研討會時間 19941215~19941217
通訊作者
國別 TWN
公開徵稿
出版型式
出處 Proceedings of 1994 International Symposium on Artificial Neural Networks，頁596-601
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