[1]李 泊,陈 诚.基于类鱼行为搜寻策略的水下传感器布置[J].南京理工大学学报(自然科学版),2019,43(02):244.[doi:10.14177/j.cnki.32-1397n.2019.43.02.018]
 Li Bo,Chen Cheng.Fish-action hunt policy for underwater sensor deployment[J].Journal of Nanjing University of Science and Technology,2019,43(02):244.[doi:10.14177/j.cnki.32-1397n.2019.43.02.018]
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基于类鱼行为搜寻策略的水下传感器布置()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
43卷
期数:
2019年02期
页码:
244
栏目:
出版日期:
2019-04-26

文章信息/Info

Title:
Fish-action hunt policy for underwater sensor deployment
文章编号:
1005-9830(2019)02-0244-06
作者:
李 泊1陈 诚2
1.南京农业大学 工学院,江苏 南京 210031; 2.江苏省农业科学院 农业信息研究所,江苏 南京 210014
Author(s):
Li Bo1Chen Cheng2
1.College of Engineering,Nanjing Agricultural University,Nanjing 210031,China; 2.Agriculture Information Institute,Jiangsu Academy Agricultural Sciences,Nanjing 210014,China
关键词:
水下传感器 Lévy分布 类鱼行为 搜寻策略 事件覆盖率
Keywords:
underwater sensors Lévy distribution fish-action hunt policy event coverage
分类号:
TP18; TP212.6
DOI:
10.14177/j.cnki.32-1397n.2019.43.02.018
摘要:
针对开放式水域中水下事件位置的稀疏和不确定特点,该文给出一种水下传感器动态分布式布置方法。指出了与传统鱼群行为有差别的类鱼行为,在此基础上给出了水下传感器搜寻策略,并形成了动态布置方法。该布置方法通过初始布置和满足Lévy分布的类鱼探索行为扩展水下传感器的搜寻空间,有效增加了水下监测系统的事件覆盖率。改进后的尾随行为既能保证对同伴行为的有效感知,又能避免节点之间的通信,提高了传感器节点能效,增加了整个监测系统的隐蔽性。
Abstract:
In view of that the events in open waters are sparse and uncertain,the dynamic distributed arrangement for underwater sensors is presented here. The fish-action model being different from the traditional fish swarm algorithm is proposed,and then the hunt policy is given based on the fish-action to form the dynamic deployment method of underwater sensors. Through initial deployment design and explore-action in the Lévy distribution,this method expands the space under exploration and increases the event coverage of underwater surveillance system. Meanwhile,the improved follow action endues sensors with the effective perception ability on others and turns off the communication among sensors. Thus,the energy efficiency of sensors is improved and the concealment of underwater surveillance system is ameliorated.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2017-11-16 修回日期:2018-05-09
基金项目:国家自然科学基金(61503187); 中央高校基本科研基金(KJQN201624)
作者简介:李泊(1988-),女,博士,讲师,主要研究方向:智能优化算法及其应用,E-mail:libo@njau.edu.cn。
引文格式:李泊,陈诚. 基于类鱼行为搜寻策略的水下传感器布置[J]. 南京理工大学学报,2019,43(2):244-249.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2019-04-26