{"title":"Research of sludge compost maturity degree modeling method based on classify support vector machine for sewage treatment","authors":"Jingwen Tian, Meijuan Gao, Hao Zhou","doi":"10.1109/GSIS.2007.4443447","DOIUrl":null,"url":null,"abstract":"Because of the complicated interaction of the sludge compost components, it makes the judging system of sludge compost maturity degree appear the non-linearity and uncertainty. According to the physical circumstances of sludge compost, a sludge compost maturity degree modeling method based on support vector machine (SVM) is presented. We select the index of sludge compost maturity degree and take the high temperature duration, moisture content, volatile solids, the value of fecal bacteria, and germination index as the judgment parameters. We construct the structure of SVM network that used for the maturity degree judgment of sludge compost, and use the genetic algorithm (GA) to optimize SVM parameters. With the ability of strong self-learning and well generalization of SVM, the modeling method can truly judge the sludge compost maturity degree by learning the index information of sludge compost maturity degree. The experimental results show that this method is feasible and effective.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"44 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Conference on Grey Systems and Intelligent Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GSIS.2007.4443447","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Because of the complicated interaction of the sludge compost components, it makes the judging system of sludge compost maturity degree appear the non-linearity and uncertainty. According to the physical circumstances of sludge compost, a sludge compost maturity degree modeling method based on support vector machine (SVM) is presented. We select the index of sludge compost maturity degree and take the high temperature duration, moisture content, volatile solids, the value of fecal bacteria, and germination index as the judgment parameters. We construct the structure of SVM network that used for the maturity degree judgment of sludge compost, and use the genetic algorithm (GA) to optimize SVM parameters. With the ability of strong self-learning and well generalization of SVM, the modeling method can truly judge the sludge compost maturity degree by learning the index information of sludge compost maturity degree. The experimental results show that this method is feasible and effective.