长江科学院院报2017，Vol.34Issue(8)：41-46,6.DOI:10.11988/ckyyb.20160419
基于改进粒子群算法的大坝监控加权统计模型
Weighted Statistical Model of Dam Monitoring Based on Improved Particle Swarm Optimization Algorithm
摘要
Abstract
The weights of all factors in weighted statistical model of dam monitoring were determined with engineering experience,which could result in the lack of the information of some factors.According to monitoring data,the regression coefficients and weights of weighted statistical model can be objectively determined by Particle Swarm Optimization algorithm,but for high dimension optimization,the algorithm has some deficiencies such as slow convergence and local minimums.In view of this,an improved Particle Swarm Optimization algorithm in consideration of the information of average location in particles is proposed.The learning factors are determined based on the information of average location in single particle and particle groups.The analysis results of earth-rock dam example show that the improved Particle Swarm Optimization algorithm enhances the ability of jumping out of the local minimum.The factors of weighted statistical model of safety monitoring for earth-rock dam are consistent in actual situation with this improved algorithm.Especially in the early stages of operation with few monitoring data,dam monitoring model based on improved Particle Swarm Optimization algorithm has better precision.The improved algorithm could be a new method of data analysis in dam monitoring field.关键词
土石坝/加权统计模型/改进粒子群算法/优化计算/权重系数Key words
earth-rock dam/weighted statistical model/improved Particle Swarm Optimization algorithm/optimization computation/weight coefficient分类
建筑与水利引用本文复制引用
王伟,徐锴,方绪顺,钟启明..基于改进粒子群算法的大坝监控加权统计模型[J].长江科学院院报,2017,34(8):41-46,6.基金项目
国家自然科学基金项目(51379129) （51379129）
水利部公益性行业科研经费项目(sg315002) （sg315002）
