摘要
针对目前三维空间传感器部署算法PSO算法存在寻优精度、全局收敛性和收敛速度不能保证的问题,提出了通过惯性权重线性递减策略与动态加速常数自适应策略改进的基于粒子群的WCPSO优化算法,有效地提高了算法的寻优精度和收敛速度。给出了算法的设计方案并进行了来袭路径未知和来袭路径预估情况下的仿真实验,仿真实验结果表明WCPSO算法的优化效果和效率都要优于改进前的PSO算法。
Since the particle swarm optimization（PSO） algorithm of three- dimensional space sensor deployment algorithm can′t guarantee the optimizing accuracy,global convergence and convergence rate,the improved PSO-based WCPSO algorithm combining inertia weight linear decreasing strategy with dynamic acceleration constant adaptive strategy is put forward to improve the optimizing accuracy and convergence rate of the algorithm effectively. The design scheme of the algorithm is given,and the simulation experiments of unknown invading path and estimated invading path were performed. The simulation experiment results show that the optimal effect and efficiency of WCPSO algorithm are superior to the PSO algorithm before improvement.
出处
《现代电子技术》
北大核心
2016年第17期132-135,139,共5页
Modern Electronics Technique
基金
四川省教育厅科研项目:基于遗传算法的传感器动态特性研究(15ZB0276)
关键词
粒子群优化算法
部署优化
传感器网络
WCPSO算法
particle swarm optimization algorithm
optimum deployment
sensor network
WCPSO algorithm
