计算机应用与软件2018，Vol.35Issue(3)：120-123,144,5.DOI:10.3969/j.issn.1000-386x.2018.03.023
量子粒子群算法在WSN三维定位中的研究
RESEARCH ON QUANTUM PARTICLE SWARM OPTIMIZATION ALGORITHM IN THREE DIMENSIONAL LOCALIZATION OF WSN
摘要
Abstract
3D-DVHoP as a classic three-dimensional localization algorithm, when the uneven distribution of nodes due to "winding"phenomenon leading to a large deviation.In order to find the minimum error between the actual distance and estimated distance of neighbor nodes and improve the localization accuracy, the existing improved algorithms are easy to fall into the local optimum or no solution.The new algorithm introduces the quantum rotation gate variation rule based on 3D-DVHoP.Modifying the individual particle rate and state by crossover mutation, we can increase the universality and ergodicity of particle search to find the global optimal solution.The simulation results show that the new algorithm can avoid the problem that the existing improved algorithms are easy to fall into the local optimum and has higher localization accuracy.关键词
无线传感网络/3D-DVHoP/量子门/粒子群Key words
WSN/3D-DVHoP/Quantum gate/Particle swarm分类
信息技术与安全科学引用本文复制引用
刘小园..量子粒子群算法在WSN三维定位中的研究[J].计算机应用与软件,2018,35(3):120-123,144,5.基金项目
国家自然科学基金面上项目(61672546) （61672546）
广东省教育厅课题立项项目(20130301064). （20130301064）
