{"title":"Research on Dynamic Monitoring and Early Warning Methods of Company Management Driven by Artificial Intelligence","authors":"Yuantian Zhu","doi":"10.1109/CSAIEE54046.2021.9543389","DOIUrl":null,"url":null,"abstract":"The rapid development of science and technology in our country has led to the rapid development of Chinese enterprises, and the scale of enterprise production has continued to expand. However, as enterprises continue to accelerate their expansion and development, it follows that a huge scale is generated during the operation of the enterprise. The amount of data is increasing, and the hidden dangers of enterprises are also escalating. With the continuous competition among enterprises, the predictive and early warning technology under artificial intelligence has become the most advantageous competitiveness among enterprises. At the same time, the immeasurable losses caused by risks have made enterprises' desire for artificial intelligence monitoring and early warning technology more intense and urgent. Nowadays, most companies are still using more traditional corporate management methods. This traditional management method has many problems: mostly based on experience and visual inspection, thus ignoring the attention to some risks that cannot be visually observed, and cannot pay attention to the current corporate risks. Quantitative analysis and evaluation of the status can not achieve the effect of accurately preventing risks, so that the potential value of a large amount of data cannot be fully explored.","PeriodicalId":376014,"journal":{"name":"2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSAIEE54046.2021.9543389","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
The rapid development of science and technology in our country has led to the rapid development of Chinese enterprises, and the scale of enterprise production has continued to expand. However, as enterprises continue to accelerate their expansion and development, it follows that a huge scale is generated during the operation of the enterprise. The amount of data is increasing, and the hidden dangers of enterprises are also escalating. With the continuous competition among enterprises, the predictive and early warning technology under artificial intelligence has become the most advantageous competitiveness among enterprises. At the same time, the immeasurable losses caused by risks have made enterprises' desire for artificial intelligence monitoring and early warning technology more intense and urgent. Nowadays, most companies are still using more traditional corporate management methods. This traditional management method has many problems: mostly based on experience and visual inspection, thus ignoring the attention to some risks that cannot be visually observed, and cannot pay attention to the current corporate risks. Quantitative analysis and evaluation of the status can not achieve the effect of accurately preventing risks, so that the potential value of a large amount of data cannot be fully explored.