人民长江2015，Vol.46Issue(18)：97-100,104,5.DOI:10.16232/j.cnki.1001-4179.2015.18.025
基于改进PSO算法和SVM的大坝监控模型研究
Study of dam safety monitoring model based on improved PSO algorithm and SVM theory
杨晓晓 1刘懿 2王超 3刘彪 3王泉1
作者信息
- 1. 河海大学 水利水电学院,江苏 南京210098
- 2. 河海大学 水文水资源学院,江苏 南京210098
- 3. 河海大学 水文水资源与水利工程科学国家重点实验室,江苏 南京210098
- 折叠
摘要
Abstract
According to the characteristics that the conventional model of dam safety early-warning is sensitive to the missing data and the forecast accuracy is prone to be affected by other factors, a model combing the improved PSO algorithm and SVM theory was proposed, which seeks the optimal parameters of SVM model through PSO algorithm. Meanwhile, the convergence de-gree is introduced and the inertia weight factor and study factor are optimized to avoid the premature convergence of PSO, so the global searching ability is improved. The establishing process of the model was introduced and the forecast accuracy was verified by actual monitoring data. With the analysis of the example, it is proved that the improved model is superior to the conventional model, and the application range of PSO algorithm is extended.关键词
变形监测/支持向量机/粒子群算法/早熟收敛Key words
deformation monitoring/SVM/PSO algorithm/premature convergence分类
建筑与水利引用本文复制引用
杨晓晓,刘懿,王超,刘彪,王泉..基于改进PSO算法和SVM的大坝监控模型研究[J].人民长江,2015,46(18):97-100,104,5.
