{"title":"Neurofuzzy inference system for diagnosis of malaria","authors":"Aayush Rastogi, N. Gupta, P. Tyagi","doi":"10.1109/CIPECH.2014.7019042","DOIUrl":null,"url":null,"abstract":"In this paper, a structure of adaptive system is proposed with the help of Neurofuzzy System (NFS) for diagnosis of Malaria. Investigation of malaria using Neurofuzzy system has been used for decision making ability based on predefined rules and learning by the backpropagation algorithm. Mapping Network in backpropagation algorithm is applied to minimize the errors in the output. Investigation of malaria by the proposed system is illustrated and good performance is achieved with maximum instant error of 0.06144.","PeriodicalId":170027,"journal":{"name":"2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIPECH.2014.7019042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, a structure of adaptive system is proposed with the help of Neurofuzzy System (NFS) for diagnosis of Malaria. Investigation of malaria using Neurofuzzy system has been used for decision making ability based on predefined rules and learning by the backpropagation algorithm. Mapping Network in backpropagation algorithm is applied to minimize the errors in the output. Investigation of malaria by the proposed system is illustrated and good performance is achieved with maximum instant error of 0.06144.