{"title":"Utilizing a new feed-back fuzzy neural network for solving a system of fuzzy equations","authors":"A. Jafarian, S. M. Nia","doi":"10.5899/2012/CNA-00096","DOIUrl":"https://doi.org/10.5899/2012/CNA-00096","url":null,"abstract":"In this paper, we intend to offer a new method based on fuzzy neural networks for finding a real solution of fuzzy equations system. Our proposed fuzzified neural network is a five-layer feed-back neural network that corresponding connection weights to output layer are fuzzy numbers. The proposed architecture of artificial neural network, can get a real input vector and calculates it's corresponding fuzzy output. In order to find the approximate solution of this fuzzy system that supposedly has a real solution, first a cost function is defined for the level sets of fuzzy output and target output. Then a learning algorithm based on the gradient descent method will be introduced that can adjust the crisp input signals. The proposed method is illustrated by several examples with computer simulations.","PeriodicalId":269623,"journal":{"name":"International Journal of Industrial Mathematics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125507016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}