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基于可控制粒子群优化的无线传感网节点定位技术; The Wireless Sensor Network Node Localization Technology Based on Controlled Particle Swarm Optimization
张源峰 ; 程恩
2013-11-28
关键词传感节点 多维标度 粒子群优化 节点定位 sensor nodes multidimensional scaling particle swarm optimization node localization
英文摘要针对传统的基于分布式加权距离的无线传感节点定位过程中,节点定位准确度低,导致节点定位误差较大的问题,提出了一种基于可控制粒子群优化的无线传感网节点定位算法.采用经典多维标度法(MdS)定位算法求得节点的初始化坐标,在传统的粒子群算法中引入粒子释放以及速度约束体系,对粒子群计算过程中粒子生成过程进行控制,根据节点定位过程中的反馈,控制粒子释放速度,并约束相应的过程,在保证最优定位的同时,可以最大程度地增强粒子种群的多样性,避免定位过程中出现局部最优现象,准确定位无线传感节点.实验结果表明:改进后的算法与原算法相比,在定位精度上有明显的提高.; In order to solve the problem of large deviation caused by the low accuracy of the node localization in the traditional wireless node localization technology,this paper proposed the new wireless sensor network node localization algorithm based on the controlled particle swarm optimization.In the paper,it used the MDS localization algorithm to get the initialized coordinate,introduced the system of particle release and speed restriction into the traditional particle swarm algorithm,controlled the particle generation process in the calculation of particle swarm,and controlled the particle release speed according to the feedback of the localization process with constraints to the related process.This paper also increased the diversity of the enhanced particle swarm to the larger extent while ensuring the optimal positioning at the same time and avoiding local optimum phenomenon appeared in the process of localization,which largely made the accuracy of the localization of the wireless sensor node.The result of the experiment shows that the localization accuracy is significantly improved in the improved algorithm,comparing with the original algorithm.; 国家自然科学基金项目(61071150)
语种zh_CN
内容类型期刊论文
源URL[http://dspace.xmu.edu.cn/handle/2288/123036]  
专题信息技术-已发表论文
推荐引用方式
GB/T 7714
张源峰,程恩. 基于可控制粒子群优化的无线传感网节点定位技术, The Wireless Sensor Network Node Localization Technology Based on Controlled Particle Swarm Optimization[J],2013.
APA 张源峰,&程恩.(2013).基于可控制粒子群优化的无线传感网节点定位技术..
MLA 张源峰,et al."基于可控制粒子群优化的无线传感网节点定位技术".(2013).
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