基于大数据的煤矿违规行为分析识别系统研究

    Research on mine violation analysis and identification system based on big data

    • 摘要: 以煤矿智慧矿山建设为背景,以监控系统联网平台海量数据为基础,通过研究Hadoop、Hive等关键核心技术,数据清洗、数据转换等数据仓库技术,数学分析模型抽象与挖掘等大数据手段,从现有海量数据中提取有价值的数据,分析其内部关联性,并对数据异常情况进行识别、分析,找出煤矿潜在的违规操作风险点,助力煤矿企业及时消除安全隐患。

       

      Abstract: Based on the construction of intelligent mine in coal mine and massive data of monitoring system networking platform, valuable data are extracted from the existing massive data and its internal relevance is analyzed by studying key core technologies such as Hadoop and Hive, data warehouse technologies such as data cleaning and data conversion, and big data means such as mathematical analysis model abstraction and mining. Extract valuable data from existing massive data, analyze its internal relevance, identify and analyze abnormal data, find out the potential risk points of illegal operation in coal mines, and help coal mining enterprises to eliminate safety risks in time.

       

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