现代电子技术2018，Vol.41Issue(7)：156-159,164,5.DOI:10.16652/j.issn.1004-373x.2018.07.036
基于粒子群优化的SVM供水管道泄漏诊断方法
PSO-SVM based leakage diagnosis method of water supply pipeline
摘要
Abstract
The leakage of water supply pipeline will cause the water resource waste and economic losses. The traditional leakage diagnosis model based on support vector machine(SVM)has the problem of uncertain parameter selection,which may cause the unstable classification result. The particle swarm optimization(PSO)algorithm is proposed for parameter optimization selection in leakage diagnosis model based on SVM.The particle swarm intelligent optimization search is used to quickly iterate the reasonable penalty parameter and kernel parameter of SVM in the overall situation,so as to make the pipeline leakage diagnosis model based on PSO-SVM optimal. The experimental results show that,in combination with the fast convergence speed of PSO global search,the method can solve the two important parameters optimization selection problem in SVM model,and improve the accuracy and efficiency of SVM classification.关键词
供水管道/泄漏诊断/支持向量机/粒子群算法/参数优化/PSO-SVMKey words
water supply pipeline/leakage diagnosis/SVM/PSO/parameter optimization/PSO-SVM分类
信息技术与安全科学引用本文复制引用
王学渊,陈志刚,钟新荣,卢宁..基于粒子群优化的SVM供水管道泄漏诊断方法[J].现代电子技术,2018,41(7):156-159,164,5.基金项目
国家自然科学基金(51004005) （51004005）
住建部资助项目(2016-K4-081) （2016-K4-081）
北京市优秀人才培养资助项目(2013D005017000013) （2013D005017000013）
北京市属高等学校高层次人才引进与培养计划项目 （）
北京市教育委员会科技计划一般项目(KM201610016017) Project Supported by National Natural Science Foundation of China(51004005),Ministry of Housing and Urban-Rural Development of the People's Republic of China(2016-K4-081),Beijing Excellent Talent Training(2013D005017000013),Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions,Beijing Municipal Commission of Education Science and Technology Plan(KM201610016017) （KM201610016017）
