吉林大学学报（理学版）2017，Vol.55Issue(3)：647-651,5.DOI:10.13413/j.cnki.jdxblxb.2017.03.32
人工蜂群算法优化支持向量机的传感器节点定位
Sensor Node Localization Based on Artificial Bee Colony Algorithm Optimizing Support Vector Machine
摘要
Abstract
In order to improve the localization effect of sensor nodes, aiming at the parameters optimization problem of support vector machine,we designed a sensor node localization model based on artificial bee colony algorithm optimizing support vector mathine.Firstly,relevant data of sensor nodes were collected,and the effective parameters were extracted.Secondly,support vector machine was used to establish sensor node localization model,and artificial bee colony algorithm was used to solve the parameter selection problem of support vector machine.Finally,sensor node localization experiment was implemented on MATLAB2014 platform.The experimental results show that the proposed model can reflect the position of current sensor nodes,and obtain the accurate positioning results of the sensor nodes.关键词
传感器节点/定位机制/特征参数/参数选择问题/人工蜂群优化算法Key words
sensor node/localization mechanism/characteristic parameter/parameter selection problem/artificial bee colony optimization algorithm分类
信息技术与安全科学引用本文复制引用
陈海霞,王连明..人工蜂群算法优化支持向量机的传感器节点定位[J].吉林大学学报（理学版）,2017,55(3):647-651,5.基金项目
吉林省科技发展计划项目(批准号:20140101198JC). （批准号:20140101198JC）
