基于Apriori算法下的矿井火灾事故预测研究

Forcast of Mine Fire Accident Based on Apriori Algorithm

应用Apriori算法完成数据挖掘模型建构,对矿井相关数据实施采集、预处理及数据挖掘,进而实现对矿井火灾事故的预测分析,获得矿井火灾事故发生率。研究结果表明,通过关联规则分析某矿井的相关数据,发现高瓦斯浓度-低流量置信度在70%左右,高瓦斯浓度-低负压置信度在61%左右,由此得出在矿井火灾事故防治中,要加强对日产量以及瓦斯浓度的控制。

The Apriori algorithm was adopted to construct a data mining model,which was then used to achieve the collection,pretreatment and mining of related data,so as to forecast and analyze the mine fire accidents,for obtaining the incidence of mine fire accidents.Results show that based on the association-rule analysis for the relevant data of a mine,it is found that the confidence for high gas concentration and low flow rate is about 70%,and the confidence for high gas concentration and low negative pressure is about 61%.It is concluded that the control of daily output and gas concentration should be strengthened for the prevention and control of mine fire accidents.