| 基于混合人工鱼群算法的传感器网络优化 |
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| 引用本文： | 廖灿星,张平,李行善,张岩.基于混合人工鱼群算法的传感器网络优化[J].北京航空航天大学学报,2010,36(3):373-377. |
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| 作者姓名： | 廖灿星 张平 李行善 张岩 |
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| 作者单位： | 北京航空航天大学,自动化科学与电气工程学院,北京100191;中国人民解放军95661部队,重庆,400030 |
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| 摘 要： | 针对传感器网络节点优化的问题,提出一种混合人工鱼群算法.该算法在人工鱼群算法优化的末段引入模式搜索法,以人工鱼搜索到的最优解作为模式搜索法的初始解,利用模式搜索法的单调搜索特性,将解引向全局极值.新算法保留了人工鱼群算法全局搜索能力强、寻优速度快的特点,使寻优精度得到了提高.仿真实验表明:混合人工鱼群算法能够有效地优化传感器网络节点部署,提高覆盖率.
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| 关 键 词： | 人工鱼群算法 模式搜索法 传感器网络 智能优化 |
| 收稿时间： | 2009-07-23 |
Optimal deployment in sensor networks based on hybrid artificial fish school algorithm |
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| Liao Canxing,Zhang Ping,Li Xingshan,Zhang Yan.Optimal deployment in sensor networks based on hybrid artificial fish school algorithm[J].Journal of Beijing University of Aeronautics and Astronautics,2010,36(3):373-377. |
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| Authors: | Liao Canxing Zhang Ping Li Xingshan Zhang Yan |
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| Institution: | 1. School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
2. Unit 95661 of PLA, Chongqing 400030, China |
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| Abstract: | A hybrid artificial fish school algorithm was presented for optimal nodes deployment of sensor networks.The hybrid artificial fish school algorithm included two phases.In speed priority phase,a suboptimal solution in the neighborhood of optimum solution was found rapidly by using the artificial fish school algorithm.In accuracy priority phase,taking the suboptimal solution as its initial solution and by using its monotonic convergence of the pattern search method,the solution to global extremum was led to.T... |
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| Keywords: | artificial intelligence pattern search method sensor networks optimization |
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