岩土工程弹塑性反分析的改进粒子群算法  

Improved Particle Swarm Optimization for Elastoplastic Back Analysis in Geotechnical Engineering

作　　者：李晓龙[1] 王复明[1] 李晓楠[2] 

机构地区：[1]郑州大学水利与环境学院,河南郑州450002 [2]中原工学院计算机学院,河南郑州450007

出　　处：《采矿与安全工程学报》2009年第1期50-54,共5页Journal of Mining & Safety Engineering

基　　金：国家杰出青年科学基金项目(19625205)

摘　　要：为了克服常规粒子群算法(PSO)应用于岩土工程弹塑性反演时搜索效率较低、计算工作量大的缺点,通过对算法中适应值比较方式和粒子运动模式的深入分析,指出了其中存在的制约搜索效率的内在因素,并提出相应修改策略,在此基础上形成一种新的改进粒子群算法(IPSO);将新算法用于岩土材料弹塑性参数反演,结果表明,与常规粒子群算法相比,改进算法明显提高了参数的搜索效率,利用较少的迭代次数就能得到满足精度要求的结果,从而减小了岩土工程弹塑性反分析的计算量,是一种可行的参数反演方法.In order to offset the disadvantages of low searching efficiency and large amount of calculation using traditional PSO for elastoplastic back analysis in geotechnical engineering,the comparison method of fitness value and the motion mode of individual particle of traditional PSO are analyzed and the internal factors which restrict searching efficiency pointed out.Then some corresponding improvement measures are proposed.On this basis,an improved PSO（IPSO） is put forward and used for elastoplastic parameters inverse.The results show that,compared with traditional PSO,the parameter searching efficiency and the convergence precision of IPSO have an obvious increase and the inverse results meeting accuracy requirements can be obtained with less number of iterations.Thus the calculation amount for elastplastic back analysis can be greatly reduced if using IPSO.So our proposed algorithm is a feasible method for elastoplastic back analysis in geotechnical engineering.

关 键 词：岩土工程 弹塑性反分析 粒子群算法 改进粒子群算法 搜索效率 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] TU45[自动化与计算机技术—控制科学与工程]