通信学报Issue(3)：1-8,8.DOI:10.11959/j.issn.1000-436x.2015076
三元相关性量子行为粒子群优化算法研究
Study of the ternary correlation quantum-behaved PSO algorithm
摘要
Abstract
In order to more effectively utilize existing information and improve QPSO’s (quantum-behaved particle swarm optimization) convergence performance, the ternary correlation QPSO (TC-QPSO) algorithm was proposed based on the analysis of the random factors in location formula. The novel algorithm changed the information independent ran-dom processing method of standard QPSO and established internal relations during particles’ own experience information, group sharing information and the distance from the particles’ current location to the population mean best position using normal copula functions.Then, the method of generating ternary correlation factors was given by using the Cholesky square root formula. The simulation results of the test functions showed that TC-QPSO algorithm outperforms the stan-dard QPSO algorithm in terms of optimization results, given that the negative linear correlation exists betweenu andr1 or u andr2.关键词
粒子群优化/量子粒子群优化/量子势阱/正态Copula函数/收敛Key words
particle swarm optimization (PSO)/quantum-behaved particle swarm optimization (QPSO)/quantum poten-tial well/normal copula function/convergence分类
信息技术与安全科学引用本文复制引用
吴涛,陈曦,严余松..三元相关性量子行为粒子群优化算法研究[J].通信学报,2015,(3):1-8,8.基金项目
国家自然科学基金资助项目(61104175)；四川省软科学研究计划基金资助项目(2012ZR0022)；四川省科技支撑计划基金资助项目(2012GZX0090)Foundation Items:The National Natural Science Foundation of China (61104175) （61104175）
Sichuan Province Soft Science Research Pro-ject(2012ZR0022)；Sichuan Province Science Support Project(2012GZX0090) （2012ZR0022）
