{"title":"A study of semiconductor industry accidents: Making predictions based on BP artificial neural networks","authors":"L. Chao, Hsu PeiChen, Wu Jianping","doi":"10.1109/IEEM.2013.6962460","DOIUrl":null,"url":null,"abstract":"This paper puts forward using BP artificial neural network to forecast semiconductor industry accidents, using optimized and quantifiable impact factors of accidents as input nodes and accident quantity as the output node. The established predictive model has 7 input parameters and 1 output parameter. This paper uses this model to predict and validate the accident occurrence circumstances of a semiconductor company and gets accurate results.","PeriodicalId":6454,"journal":{"name":"2013 IEEE International Conference on Industrial Engineering and Engineering Management","volume":"16 1","pages":"492-496"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Industrial Engineering and Engineering Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM.2013.6962460","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
This paper puts forward using BP artificial neural network to forecast semiconductor industry accidents, using optimized and quantifiable impact factors of accidents as input nodes and accident quantity as the output node. The established predictive model has 7 input parameters and 1 output parameter. This paper uses this model to predict and validate the accident occurrence circumstances of a semiconductor company and gets accurate results.