{"title":"软件的数据分析和预测破产的组织在燃料和能源综合体","authors":"Alla V. Vinogradova, A. Lazarev, P. Kharlamov","doi":"10.1109/REEPE51337.2021.9388039","DOIUrl":null,"url":null,"abstract":"At the present stage of the global economy development, identifying and predicting unfavourable trends in the organization’s development, including the prediction of bankruptcy, is becoming extremely important. The most accurate prediction can be made using various software applications. The paper describes the software for data analysis and prediction of bankruptcy of organizations in the fuel and energy complex, developed by the authors, its algorithm and modular structure. Its principle of operation is based on predicting the Altman’s Z-Score values in the medium term for the organization of the sector using machine learning, neural networks, and fuzzy models.","PeriodicalId":272476,"journal":{"name":"2021 3rd International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Software for data analysis and prediction of bankruptcy of organizations in the fuel and energy complex\",\"authors\":\"Alla V. Vinogradova, A. Lazarev, P. Kharlamov\",\"doi\":\"10.1109/REEPE51337.2021.9388039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"At the present stage of the global economy development, identifying and predicting unfavourable trends in the organization’s development, including the prediction of bankruptcy, is becoming extremely important. The most accurate prediction can be made using various software applications. The paper describes the software for data analysis and prediction of bankruptcy of organizations in the fuel and energy complex, developed by the authors, its algorithm and modular structure. Its principle of operation is based on predicting the Altman’s Z-Score values in the medium term for the organization of the sector using machine learning, neural networks, and fuzzy models.\",\"PeriodicalId\":272476,\"journal\":{\"name\":\"2021 3rd International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 3rd International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/REEPE51337.2021.9388039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/REEPE51337.2021.9388039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Software for data analysis and prediction of bankruptcy of organizations in the fuel and energy complex
At the present stage of the global economy development, identifying and predicting unfavourable trends in the organization’s development, including the prediction of bankruptcy, is becoming extremely important. The most accurate prediction can be made using various software applications. The paper describes the software for data analysis and prediction of bankruptcy of organizations in the fuel and energy complex, developed by the authors, its algorithm and modular structure. Its principle of operation is based on predicting the Altman’s Z-Score values in the medium term for the organization of the sector using machine learning, neural networks, and fuzzy models.