基于灰色关联理论的煤与瓦斯突出预测指标的优选  

Optimization of Coal and Gas Outburst Prediction Indexes Based on Grey Relational Theory

作　　者：高振勇 

机构地区：[1]中煤科工集团重庆研究院有限公司,重庆400037

出　　处：《煤炭技术》2014年第4期51-54,共4页Coal Technology

摘　　要：为实现煤与瓦斯突出的准确预测,减少突出预测的工作量,依据灰色关联理论,对试验矿煤与瓦斯突出预测的3个指标S、Δh2和K1进行灰色关联分析,确定各指标对煤与瓦斯突出的灰色关联度和敏感性。结果表明突出预测指标K1对该矿煤与瓦斯突出的灰色关联度最大,敏感性最高,可作为该矿突出预测的最优指标。In order to make coal and gas outburst prediction accurately through the least workloads,based on grey relational theory,confirming the grey relational and sensitive indexes of the three coal and gas outburst prediction indexes S,Δh2 and K1 by grey relational analysis of the testing mine.The final result shows that the prediction indexes K1 has the biggest grey relational and sensitive degrees and indicates that K1 is the best prediction index of coal and gas outburst on the testing mine.

关 键 词：灰色关联度 煤与瓦斯突出 预测指标 敏感性优选 

分 类 号：TD713[矿业工程—矿井通风与安全]