| 基于神经网络和遗传算法的无功优化设计 |
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| 引用本文： | 李清政,钟建伟.基于神经网络和遗传算法的无功优化设计[J].湖北民族学院学报(哲学社会科学版),2006,24(3):236-238. |
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| 作者姓名： | 李清政 钟建伟 |
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| 作者单位： | 湖北民族学院信息工程学院 湖北恩施445000 |
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| 摘 要： | 无功优化是一个复杂的混合优化问题,传统方法较难获得全局最优解.文中提出了将并行遗传算法和Hopfield网络相结合的算法.该方法利用遗传算法的并行搜索和解空间搜索的优点进行网络参数的选取,并采用Hopfield网络简单、快速、规范的优点来优化样本空间,以取得整体的优化效率.
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| 关 键 词： | 遗传算法 Hopfield神经网络 无功优化算法 |
| 文章编号： | 1008-8423(2006)03-0236-03 |
| 修稿时间： | 2006年4月13日 |
Design of Reactive Power Optimization System Based on Neural Network and Genetic Algorithm |
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| LI Qing-zheng,ZHONG Jian-wei.Design of Reactive Power Optimization System Based on Neural Network and Genetic Algorithm[J].Journal of Hubei Institute for Nationalities(Natural Sciences),2006,24(3):236-238. |
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| Authors: | LI Qing-zheng ZHONG Jian-wei |
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| Abstract: | Reactive power optimization is a complicated hybrid problem.It is very difficult to find the optimizing solution as a whole with the traditional method.A parallel genetic algorithm combined with Hopfield neural network is proposed in this article.In order to get the optimizing efficiency as a whole,this method not only chooses net parameters by making use of the merit of parallel searching and solution spaced searching,but also improves the sample space with the merit of simplicity,quickness and standardization of Hopfield neural network. |
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| Keywords: | genetic algorithm Hopfield neural network reactive power optimization algorithm |
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