基于大数据的煤矿瓦斯事故关键要素分析

Analysis on key factors of coal mine gas accident based on big data

针对危害性大、易造成群死群伤的瓦斯事故,运用大数据理念和方法,搜集海量事故相关资料,并通过构建VSM向量空间模型,实现事故相关资料的信息化、数据化。在通用词典和专业词典基础上,运用TFIDF算法,经过词频统计、特征过滤、特征合并,形成事故特征词典。在事故特征词典基础上,进一步运用语料库进行特征词典过滤,并最终通过Delphi法实现煤矿瓦斯事故关键要素识别。

According to a high danger and mass injuries caused by the mine gas accident, a big data idea and method was applied to collect the related information of the mass accidents. With the establishment on a vector space modal （VSM）, the informatization and digitalization of the accident related information were realized. Based on the general dictionary and the professional dictionary, a TFIDF algorithm was applied to form an accident characteristic dictionary with the word frequency statistics, characteristics filtration and the characteristics combination. Based on the accident characteristics dictionary, a corpus was further applied to the filtration of the characteristics dictionary. Finally the Delphi method could be applied to realize the key factor identification of the mine gas accident.