{"title":"基于用电数据的小微企业运行指标监测研究","authors":"Qing Dai, Wende Zhuang, Jun Yang","doi":"10.1109/ICOCWC60930.2024.10470626","DOIUrl":null,"url":null,"abstract":"The research of operation indicators plays an important role in intelligent monitoring of small and micro enterprises, but there is a problem of inaccurate monitoring. The traditional regression algorithm cannot solve the research problem of monitoring operation indicators in intelligent monitoring of small and micro enterprises, and the detection effect is not satisfactory. Therefore, this paper proposes a research on monitoring the operation indicators of small and micro enterprises based on electrical data monitoring, and analyzes the research on the operation indicators of small and micro enterprises. Firstly, the power system theory is used to locate the influencing factors, and the indicators is divided according to the requirements of the research of operation indicators, so as to reduce the interference factors in the research of operation indicators. Then, the power system theory is used to form a research scheme for monitoring the operation index of electrical data, and the research results of the operation index is comprehensively analyzed. The MATLAB simulation results show that under certain evaluation standards, electrical data monitoring is superior to the traditional regression method in terms of research accuracy of operation indicators and research influencing factor time of operation indicators.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"10 5","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Monitoring the Operation Indicators of Small and Micro Enterprises Based on Electricity Consumption Data\",\"authors\":\"Qing Dai, Wende Zhuang, Jun Yang\",\"doi\":\"10.1109/ICOCWC60930.2024.10470626\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The research of operation indicators plays an important role in intelligent monitoring of small and micro enterprises, but there is a problem of inaccurate monitoring. The traditional regression algorithm cannot solve the research problem of monitoring operation indicators in intelligent monitoring of small and micro enterprises, and the detection effect is not satisfactory. Therefore, this paper proposes a research on monitoring the operation indicators of small and micro enterprises based on electrical data monitoring, and analyzes the research on the operation indicators of small and micro enterprises. Firstly, the power system theory is used to locate the influencing factors, and the indicators is divided according to the requirements of the research of operation indicators, so as to reduce the interference factors in the research of operation indicators. Then, the power system theory is used to form a research scheme for monitoring the operation index of electrical data, and the research results of the operation index is comprehensively analyzed. The MATLAB simulation results show that under certain evaluation standards, electrical data monitoring is superior to the traditional regression method in terms of research accuracy of operation indicators and research influencing factor time of operation indicators.\",\"PeriodicalId\":518901,\"journal\":{\"name\":\"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)\",\"volume\":\"10 5\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOCWC60930.2024.10470626\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOCWC60930.2024.10470626","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Monitoring the Operation Indicators of Small and Micro Enterprises Based on Electricity Consumption Data
The research of operation indicators plays an important role in intelligent monitoring of small and micro enterprises, but there is a problem of inaccurate monitoring. The traditional regression algorithm cannot solve the research problem of monitoring operation indicators in intelligent monitoring of small and micro enterprises, and the detection effect is not satisfactory. Therefore, this paper proposes a research on monitoring the operation indicators of small and micro enterprises based on electrical data monitoring, and analyzes the research on the operation indicators of small and micro enterprises. Firstly, the power system theory is used to locate the influencing factors, and the indicators is divided according to the requirements of the research of operation indicators, so as to reduce the interference factors in the research of operation indicators. Then, the power system theory is used to form a research scheme for monitoring the operation index of electrical data, and the research results of the operation index is comprehensively analyzed. The MATLAB simulation results show that under certain evaluation standards, electrical data monitoring is superior to the traditional regression method in terms of research accuracy of operation indicators and research influencing factor time of operation indicators.