{"title":"Research on Crisis Warning Model of Enterprise Finance Based on Deep Learning","authors":"Yeming Chen, Xinyuan Han","doi":"10.1145/3448748.3448775","DOIUrl":null,"url":null,"abstract":"Looking for an effective financial crisis early warning method is of great significance to China's economy and company development. This paper fully considers the internal factors that affect the financial situation of enterprises, and establishes a financial early warning index system composed of eighteen secondary indicators. This paper uses LSTM neural network in deep learning to establish an early warning model. The results show that the prediction accuracy of the early warning model based on deep learning can reach more than 85%.","PeriodicalId":115821,"journal":{"name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3448748.3448775","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
Looking for an effective financial crisis early warning method is of great significance to China's economy and company development. This paper fully considers the internal factors that affect the financial situation of enterprises, and establishes a financial early warning index system composed of eighteen secondary indicators. This paper uses LSTM neural network in deep learning to establish an early warning model. The results show that the prediction accuracy of the early warning model based on deep learning can reach more than 85%.