| 周荣敏,买文宁,雷延峰,林性粹.自压式树状管网神经网络优化设计[J].水利学报,2002,33(2):0066-0071 |
| 自压式树状管网神经网络优化设计 |
| Artificial neural networks optimal design of gravity tree pipe network |
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| DOI： |
| 中文关键词: 树状管网 人工神经网络 优化设计 两级优化算法 |
| 英文关键词: tree pipe network artificial neural networks optimal design two-level optimal algorithm |
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| 摘要点击次数: 1900 |
| 全文下载次数: 164 |
| 中文摘要: |
| 应用Hopfield神经网络模型的优化计算原理与方法, 建立了自压式树状管网神经网络优化设计模型, 并用计算机软件模拟方法求解. 研究表明: 人工神经网络法是快速求解自压式树状管网非线性规划模型的一种新方法, 结合两级优化算法可以实现树状管网全局最优设计. |
| 英文摘要: |
| Based on the optimal computation theory and Hopfield's artificial neural network method, an artificial neural network optimal design model for simulation of gravity tree pipe network is established. The application shows that it is a new way to solve the nonlinear programming model of gravity tree pipe network and is able to realize the overall optimal design of the network if combining with two-level optimal algorithm. |
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