基于Apriori算法的煤自燃影响因素关联挖掘

Association Mining of Influencing Factors of Coal Spontaneous Combustion Based on Apriori Algorithm

针对煤自燃发火灾害占矿井火灾的90%以上,严重制约井下安全生产问题,分析了煤自燃机理和煤自燃的发火因子,提出有别于先前煤自燃指标关联关系的判定方法,根据数据挖掘的流程建立了煤自燃影响因素关联规则分析模型,基于数据挖掘Apriori算法对煤自燃参数进行结合和关联分析,并计算出支持度为30%的高频项目组和项集之间的潜在关联,揭示煤自燃发火预警防治的优势,通过Apriori算法进一步提高了煤自燃预测的准确性。

The coal spontaneous combustion disaster accounts for more than 90%of the mine fire,which seriously restricts the safety of underground production.The prediction of coal spontaneous combustion has become an important means to prevent and control the mine fire.The mechanism of coal spontaneous combustion and the ignition factors of coal spontaneous combustion were analyzed.A method to judge the correlation between the indexes of coal spontaneous combustion which is different from the previous ones was put forward.According to the process of data mining,the association rule analysis model of coal spontaneous combustion was established.Based on the data mining Apriori algorithm,the coal spontaneous combustion parameters was combined and analyzed,and the potential association was calculated between the high-frequency project group and the item set with the support degree of 30%,the advantages of coal spontaneous combustion early warning and prevention were revealed,and the accuracy of coal spontaneous combustion prediction was improved through the Apriori algorithm.