微型机与应用2017，Vol.36Issue(8)：63-66,4.DOI:10.19358/j.issn.1674-7720.2017.08.020
一种改进的粒子群算法在WSN中的定位研究
Research on the positioning of an improved particle swarm algorithm in WSN
傅彬1
作者信息
- 1. 绍兴职业技术学院,浙江 绍兴 312000
- 折叠
摘要
Abstract
Aiming at node positioning in wireless sensor network, this paper adopts RSSI measuring technology to measure the distance between unknown nodes, and uses particle swarm algorithm for optimization.Aiming at the deficiency of particle swarm algorithm, this paper firstly introduces dynamic disturbance factors and penalty functions to improve the performance of the algorithm, and then it adopts the distance error modification and modification positioning error model to optimize the effect of node optimization.Through comparing basic particle swarm algorithm in the simulation experiment, good effects have been achieved in the algorithm's convergence performance and positioning accuracy, improving the positioning effect of the node.关键词
无线传感网/动态扰动因子/惩罚函数Key words
wireless sensor network/dynamic disturbance factor/penalty function分类
计算机与自动化引用本文复制引用
傅彬..一种改进的粒子群算法在WSN中的定位研究[J].微型机与应用,2017,36(8):63-66,4.
