计算机技术与发展Issue(4)：200-203,4.DOI:10.3969/j.issn.1673-629X.2015.04.046
基于PSO算法的洪水预报模型研究
Research on Flood Forecasting Model Based on PSO
摘要
Abstract
Influenced by the Sichuan basin and the north Qinling mountains, there are many rivers that flooding frequently occurs in Dazhou. Every time,floods bring huge economic loss and heavy casualties to the government and people. Taking Zhou River in Dazhou City,Sichuan Province,as the study objects,use the monthly average flow as flood properties collected by Daxian hydrological stations, a neural network based on PSO algorithm is proposed,and a flood forecasting model is established. By the simulation experiments,the forecast accuracy is higher than traditional BP neural network,the prediction result is reasonable with small relative error,fast convergence rate and high prediction accuracy. It will help flood control departments to predict flood flow effectively and reduce the risks of flooding, and also can provide some reference opinions to flood control work in Dazhou.关键词
BP神经网络/粒子群算法/洪水流量/洪水预报Key words
BP neural network/particle swarm optimization/flood flow/flood forecasting分类
信息技术与安全科学引用本文复制引用
侯翔,廖小平..基于PSO算法的洪水预报模型研究[J].计算机技术与发展,2015,(4):200-203,4.基金项目
四川省教育科技2011年面上项目(11ZB139) （11ZB139）
达州市2011年科技攻关项目(JCY1117) （JCY1117）
四川文理学院2013年科研项目(2013Z002Y) （2013Z002Y）
