Displacement Back-analysis of rock-fill dam based on Particle Swarm Optimization and Genetic Neural Network Algorithm

摘要：

In view of the complexity of Back Analysis of rockfill material parameter, this paper uses genetic algorithm optimization BP neural network weights and threshold, simulated finite element calculation of rockfill dam by genetic neural network, combined with the theory of particle swarm optimization algorithm, and has realized inverse analysis of particle swarm optimization and genetic neural network.The results showed that: the simulation result coincides well with the experimental result, and inversion results could meet the computing requirements. This method can be widely used to solve various complicated engineering problems that target functions cant be expressed by apparent functions of decisive variables.

关键词： component particle swarm optimization algorithm genetic neural network algorithm face rock-fill dam inversion analysis

作者: Qiao Yan ChangBin Wu Songzhao LV MingLiang Bi

作者单位: China Three Gorges University College of Hydraulic and Environmental Engineering Yichang,China Hubei Huaqing Electric Co., Ltd EnShi, China China Three Gorges Corporation Yichang.China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 377-380

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）