摘要
顶板事故是我国煤矿安全生产中的重大隐患,开展顶板灾害事故安全评价,识别顶板灾害危险性是煤矿安全生产亟待解决的问题。本文在文献调研的基础上,对影响顶板灾害的影响因素进行分析,从自然因素、技术因素和管理因素三个方面构建了顶板灾害安全评价指标体系,结合专家意见对各评价指标进行量化,采用K-均值聚类与贝叶斯判别的方法对我国顶板灾害安全水平进行评价,以我国煤矿实际样本数据为研究对象开展实证分析。研究结果表明:基于K-均值聚类与贝叶斯判别的煤矿顶板安全评价方法具有较高的准确度,能够用于定量化描述煤矿顶板灾害危险,具有一定的应用前景。
Roof accident is a major hidden danger in the safety production of coal mines in China.It is an urgent problem to carry out the safety assessment of roof disaster and identify the risk of roof disaster.On the basis of literature research,this paper analyzes the influencing factors of roof disaster,constructs the safety evaluation index system of roof disaster from three aspects of natural factors,technical factors and management factors,quantifies each evaluation index by combining expert opinions,and evaluates the safety level of roof disaster in China by K-means clustering and Bayesian discrimination.The actual sample data of coal mine is the research object to carry out empirical analysis.The research results show that the safety evaluation method based on K-means clustering and Bayesian discrimination has high accuracy and can be used to quantitatively describe the risk of coal mine roof disaster,which has a certain application prospect.
作者
李世科
LI Shike(School of Computer Engineering,Henan Institute of Economics and Trade,Zhengzhou 450046,China)
出处
《中国矿业》
北大核心
2020年第4期131-135,共5页
China Mining Magazine
基金
河南省科学技术厅的校企合作项目资助(编号:豫科鉴委字〔2016〕第113号)。
关键词
顶板灾害事故
K-均值聚类
量化
贝叶斯判别
煤矿
roof disaster accident
K-means clustering
quantification
Bayesian discrimination
coal mine
