基于粒子算法的无线传感器网络覆盖优化作者：张红霞来源：《现代电子技术》2017年第09电子表单系统
期 摘 要： 北京百泰克传统无线传感器网络覆盖优化方法所选算法的结构不合理，使其覆盖能力、迭代能力和有效性无法维系网络基本功能，为此提出粒子算法的无线传感器网络覆盖优化方法。通过构建无线传感器网络认知模型，将网络覆盖优化工作转化成求取目标物体最大覆盖几率问题，使用粒子算法对模型进行编码，利用模型适应度函数给出的约束值对网络节点位置进行更新，实现对无线传感器网络覆盖率的优化。通过分析仿真实验结论可知，与传统方法相比，该方法具有更强的覆盖能力、迭代能力和有效性。
关键词： 粒子算法； 无线传感器网络； 覆盖优化方法； 模型适应度函数
中空板封边机
中图分类号： TN711⁃34； TP212.9 文献标识码： A 文章编号： 1004⁃373X（2017）09⁃0050⁃04
Abstract： The algorithm selected by the traditional wireless sensor network coverage
optimization method has unreasonable structure，格宾笼挡墙 which makes its coverage ability， iteration ability and effectiveness incapable of sustaining the network basic functions纸浆模具， therefore a wireless sensor network coverage optimization method based on particle swarm optimization algorithm is proposed. The cognitive model of the wireless sensor network is constructed to convert the network coverage optimization into the getting of the maximum coverage probability of the target object， and encoded with the particle swarm optimization algorithm. The constraint value given by the model fitness function is used to update the location of network node， so as to optimize the coverage probability of the wireless sensor network. The simulation experiment conclusion indicates， in comparison with the traditional methodsfirmicutes， the method has higher coverage ability， iteration ability and effectiveness.
