辽宁工程技术大学学报（自然科学版）Issue(3)：311-315,5.
概率积分法参数反演的文化-随机粒子群优化算法
Random PSO embedded cultural framework for parameters inversion of probability-integral method
摘要
Abstract
To solve the divergence problem of parameters inversion in probability-integral method, a novel algorithm called random PSO embedded cultural framework (CA-rPSO) is proposed in this study through integrating PSO into the framework of cultural algorithm (CA). In CA-rPSO, the evolving algorithms of belief space and population space are represented with random PSO and PSO respectively, forming independent and parallel “dual evolution-dual promotion” mechanism. Subsequently, selecting the least sum square of errors as inversion criterion, the fitness function is then established so as to inverse the parameters of probability-integral method. The case study results show that in a traditional surface movement observation station, the parameters inversions of probability-integral method based on CA-rPSO acheive a convergence rate of 1, which indicates that the algorithm has a high practicability. The study is of significance for other complex mining problems with parameters optimization.关键词
开采沉陷/地表移动观测站/概率积分法/地表移动参数/参数反演/粒子群优化/文化算法/智能优化Key words
mining subsidence/surface movement observation station/probability-integral method/parameters of surface movement/parameters inversion/PSO/cultural algorithm/intelligent optimization分类
矿业与冶金引用本文复制引用
王正帅,邓喀中,康建荣..概率积分法参数反演的文化-随机粒子群优化算法[J].辽宁工程技术大学学报（自然科学版）,2013,(3):311-315,5.基金项目
国家自然科学基金资助项目(40772191) （40772191）
国土环境与灾害监测国家测绘局重点实验室开放基金资助项目(LEDM2011B10) （LEDM2011B10）
