传感技术学报2017，Vol.30Issue(8)：1252-1257,6.DOI:10.3969/j.issn.1004-1699.2017.08.021
基于佳点集的蝙蝠定位算法在WSN中应用
A Positioning Algorithm Based on Bat Algorithm andGood-Point Setsin the Application of WSN
摘要
Abstract
In order to solve the problem that node localization error in wireless sensor network(WSN)is large,this paper proposes a new bat positioning algorithm based on good point set.In the improved algorithm,the bat population individual is optimized by the good point set method,which can effectively improve the population diversity and prevent the algorithm from falling into the local optimum;The method by introducing tribal mechanism and adaptive updating can effectively avoid attracting the local optimal solution and expedite the convergence speed;Reconstructing the tribe by pareto classification can avoid eliminating the isolated outstanding individuals,enhance the generalization ability and improve the algorithm precision.By the simulation experiments on MATLAB,the results show that the improved algorithm has good convergence and searching performance,also reduces the influence of ranging error on positioning,and improves the nodes positioning accuracy.The algorithm is simple in implementation,high in precision and high in practical value.关键词
蝙蝠算法/佳点集/部落机制/WSNKey words
bat algorithm/good-point set/tribal mechanism/WSN分类
信息技术与安全科学引用本文复制引用
谢国民,干毅军,丁会巧..基于佳点集的蝙蝠定位算法在WSN中应用[J].传感技术学报,2017,30(8):1252-1257,6.基金项目
国家自然科学基金项目(51274118) （51274118）
辽宁省重点实验室项目(LJZS003) （LJZS003）
辽宁省教育厅基金项目(UPRP20140464) （UPRP20140464）
