人工蜂群算法优化支持向量机的传感器节点定位

摘要

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.%为了提高传感器节点的定位效果,针对支持向量机参数优化问题,设计一种人工蜂群算法优化支持向量机的传感器节点定位模型.首先采集传感器节点的相关数据,提取有效参数;然后采用支持向量机建立传感器节点定位模型,并采用人工蜂群算法解决支持向量机的参数选择问题;最后在MTALAB2014平台进行传感器节点定位实验.实验结果表明,该模型可以反映当前传感器节点的位置,获得较精准的传感器节点定位结果.