Optimization inversion for mechanical parameters of concrete dam based on GA-APSO mixed penalty model

被引：6

作者：

Wei, Bowen ^{[1
,2
]}

Xu, Zhenkai ^{[1
]}

Li, Huokun ^{[1
]}

Jiang, Zhenxiang ^{[1
]}

Peng, Shengjun ^{[3
]}

机构：

[1] School of Civil Engineering and Architecture, Nanchang University, Nanchang

[2] College of Water Conservancy and Hydropower, Hohai University, Nanjing

[3] Jiangxi Provincial Institute of Water Science, Nanchang

来源：

Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) | 2015年 / 46卷 / 11期

基金：

中国国家自然科学基金;

关键词：

Concrete dam; Genetic algorithm; Mixed penalty function; Optimization inversion; Particle swarm optimization;

D O I：

10.11817/j.issn.1672-7207.2015.11.031

中图分类号：

学科分类号：

摘要：

Based on the method of mixed penalty function and considering the multi-objective optimization problem in the back analysis of rheological parameter of concrete dam, a new unconstrained single-objective optimization function was built. In order to offset the disadvantages of low searching efficiency in traditional optimization algorithm, the particle swarm optimization(PSO), which introducing self-adaptive factor and genetic algorithm(GA) were hybridized to construct a new global optimization inversion method according to their compatibility and algorithm complementary. This inversion method was established on a self-adaptive genetic particle swarm algorithm(GA-APSO), and the program of back analysis was coded, in which ANSYS finite element program was embedded as a module. The results of fore analysis and back analysis to the dam show that the optimization inversion method possesses good global search capability, a faster convergence rate and higher dam optimization inversion efficiency. This method can be applied to other dam types and the mechanical parameters of rock slope. © 2015, Central South University of Technology. All right reserved.

引用

页码：4211 / 4217

页数：6

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