电讯技术Issue(9)：1249-1253,5.DOI:10.3969/j.issn.1001-893x.2014.09.014
基于改进K-means聚类和量子粒子群算法的多航迹规划
Multiple Route Planning Based on Improved K-means Clustering and Quantum-behaved Particle Swarm Optimization
摘要
Abstract
For the problem of multiple routes planning to realize the weapon cooperation in complex envi-ronment,K-means clustering is improved by an exclusion mechanism which generates the initial cluster centers. A method combining quantum-behaved particle swarm optimization( QPSO) with K-means cluste-ring is proposed and applied to 3-D multiple routes planning of unmanned aerial vehicle( UAV) . The im-proved algorithm solves the problem of falling in local best and improves the clustering accuracy. It classi-fies the particles to several subgroups. Then every subgroup is optimized by QPSO so as to generate a feasi-ble route. Finally,multiple and dispersive routes are constituted. Simulation proves that the improved algo-rithm can assure the variety of subgroups and generates feasible and diverse routes.关键词
无人机/多航迹规划/排挤机制/量子粒子群优化/K-means聚类Key words
UAV/multiple routes planning/exclusion mechanism/quantum-behaved particle swarm opti-mization(QPSO)/K-means clustering分类
信息技术与安全科学引用本文复制引用
董阳,王瑾,柏鹏..基于改进K-means聚类和量子粒子群算法的多航迹规划[J].电讯技术,2014,(9):1249-1253,5.基金项目
陕西省电子信息系统综合集成重点实验室基金资助项目(201102Y02) （201102Y02）
国家部委基金项目(51310020401)Foundation Item:Foundation of Shaanxi Province Key Laboratory for Electronic Information Systems Synthesis Integration(201102Y02) （51310020401）
Pro-ject Supported by Ministry of China (No.51310020401) （No.51310020401）
