{"title":"大数据作为选煤厂的产物:以煤炭为例的现实与展望","authors":"Alexei Gvishiani, Izabella Nikitina, Igor Aleshin","doi":"10.2205/2023es000862","DOIUrl":null,"url":null,"abstract":"The article examines the current and future flow of preparation's plant production processes and how they contribute to the generation of Big Data. It is shown that as the level of automation in the plant increases, the data produced becomes more extensive and varied. At the same time, it is possible to achieve a level when the generated information flows meet the criteria of the Big Data. As a basic example, a typical coal processing plant is used. The main sources, volumes, variety and speeds of data transfer to the processing plant are described and analyzed.","PeriodicalId":44680,"journal":{"name":"Russian Journal of Earth Sciences","volume":"46 1","pages":"0"},"PeriodicalIF":0.7000,"publicationDate":"2023-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Big Data as a Product of the Preparation Plant: Reality and Prospects in the Case of Coal\",\"authors\":\"Alexei Gvishiani, Izabella Nikitina, Igor Aleshin\",\"doi\":\"10.2205/2023es000862\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article examines the current and future flow of preparation's plant production processes and how they contribute to the generation of Big Data. It is shown that as the level of automation in the plant increases, the data produced becomes more extensive and varied. At the same time, it is possible to achieve a level when the generated information flows meet the criteria of the Big Data. As a basic example, a typical coal processing plant is used. The main sources, volumes, variety and speeds of data transfer to the processing plant are described and analyzed.\",\"PeriodicalId\":44680,\"journal\":{\"name\":\"Russian Journal of Earth Sciences\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Russian Journal of Earth Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2205/2023es000862\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Journal of Earth Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2205/2023es000862","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Big Data as a Product of the Preparation Plant: Reality and Prospects in the Case of Coal
The article examines the current and future flow of preparation's plant production processes and how they contribute to the generation of Big Data. It is shown that as the level of automation in the plant increases, the data produced becomes more extensive and varied. At the same time, it is possible to achieve a level when the generated information flows meet the criteria of the Big Data. As a basic example, a typical coal processing plant is used. The main sources, volumes, variety and speeds of data transfer to the processing plant are described and analyzed.