计算机应用与软件Issue(10)：144-147,187,5.DOI:10.3969/j.issn.1000-386x.2015.10.033
人工鱼群算法优化支持向量机的无线传感器网络节点定位
WIRELESS SENSOR NETWORKS NODE LOCALISATION BASED ON AFSA-SVM
摘要
Abstract
In order to improve localisation precision of wireless sensors,aiming at the optimisation of support vector machine (SVM)pa-rameters,in this paper we propose the sensor node localisation method AFSA-SVM,which optimises SVMwith artificial fish swarm algorithm (AFSA).First,the method constructs the study samples of wireless sensors localisation model,and then uses SVMto build the node local-isation model,and employs AFSA to simulate the behaviours of fish swarm foraging,clustering and rear-ending for finding the optimal SVM parameters,finally the simulation experiment is used to test the performance of node localisation.Results show that compared with other local-isation methods,AFSA-SVMimproves the precision of sensor nodes localisation and has certain practical applied values.关键词
无线传感器网络/节点定位/支持向量机/人工鱼群算法Key words
Wireless sensor networks/Node localisation/SVM/Artificial fish swarm algorithm分类
信息技术与安全科学引用本文复制引用
谭军..人工鱼群算法优化支持向量机的无线传感器网络节点定位[J].计算机应用与软件,2015,(10):144-147,187,5.基金项目
广西教育厅科研项目（2013LX149）。 （）
