{"title":"数据趋势预测的统计信息分析","authors":"A. Sherstneva, O. Sherstneva","doi":"10.1109/UralCon49858.2020.9216276","DOIUrl":null,"url":null,"abstract":"The article considers organizational principles of the reporting and management system. The indicators are classified by two areas, service level and profitability. Based on these indicators, a conclusion is drawn about the system's productivity. The range of statistics needed to evaluate performance is defined. The relationship between observed statistical indicators and estimated ones is performed. A comparison between observed and estimated waiting times in different groups is shown in graphical form. The detailed processing of the selected process segments is given. In terms of opportunities the article prompts to choose approach for implementation the activity. The article aims to propose an algorithm implementation, estimate performance indicators and data trend forecasting.","PeriodicalId":230353,"journal":{"name":"2020 International Ural Conference on Electrical Power Engineering (UralCon)","volume":"32 8-9","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of Statistical Information for Data Trend Forecasting\",\"authors\":\"A. Sherstneva, O. Sherstneva\",\"doi\":\"10.1109/UralCon49858.2020.9216276\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article considers organizational principles of the reporting and management system. The indicators are classified by two areas, service level and profitability. Based on these indicators, a conclusion is drawn about the system's productivity. The range of statistics needed to evaluate performance is defined. The relationship between observed statistical indicators and estimated ones is performed. A comparison between observed and estimated waiting times in different groups is shown in graphical form. The detailed processing of the selected process segments is given. In terms of opportunities the article prompts to choose approach for implementation the activity. The article aims to propose an algorithm implementation, estimate performance indicators and data trend forecasting.\",\"PeriodicalId\":230353,\"journal\":{\"name\":\"2020 International Ural Conference on Electrical Power Engineering (UralCon)\",\"volume\":\"32 8-9\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Ural Conference on Electrical Power Engineering (UralCon)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UralCon49858.2020.9216276\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Ural Conference on Electrical Power Engineering (UralCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UralCon49858.2020.9216276","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of Statistical Information for Data Trend Forecasting
The article considers organizational principles of the reporting and management system. The indicators are classified by two areas, service level and profitability. Based on these indicators, a conclusion is drawn about the system's productivity. The range of statistics needed to evaluate performance is defined. The relationship between observed statistical indicators and estimated ones is performed. A comparison between observed and estimated waiting times in different groups is shown in graphical form. The detailed processing of the selected process segments is given. In terms of opportunities the article prompts to choose approach for implementation the activity. The article aims to propose an algorithm implementation, estimate performance indicators and data trend forecasting.
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