摘要
研究煤与瓦斯突出风险的准确预警问题。煤与瓦斯突出会导致矿井内的相关区域承受压力改变,在大区域的矿井环境下,对风险决策的贡献程度也不同,不同局部对风险决策的贡献很难准确量化。当前的煤与瓦斯突出风险检测模型多是采用同一压力阀值系数进行监测,没有考虑矿井下不同区域承压给塌方风险带来的正向影响和区域之间的承压关联性,很难形成科学的决策。提出基于信息增益决策树算法的煤与瓦斯突出风险预测模型。对煤与瓦斯分布区域进行有效的分割处理,获取大量的煤与瓦斯子区域。运用区域构建一种增益决策树,针对上述子区域进行煤与瓦斯突出风险预警。实验结果表明,利用改进模型进行煤与瓦斯风险预警,能够极大提高煤与瓦斯风险预警的准确性,为采矿安全提供保障。
This study proposed a risk prediction model of coal and gas outburst based on information gain decision tree algorithm. First, effective segmentation process was applied in distribution area of coal and gas to obtain a wide range of coal and gas sub-region. Then, the area was used to construct a gain decision tree for risk warning of coal and gas outburst in the sub-region. Experimental results show that the improved model of coal and gas risk warning can greatly improve the accuracy of risk warning of coal and gas and provide protection for mining safety.
出处
《计算机仿真》
CSCD
北大核心
2014年第3期414-417,共4页
Computer Simulation
基金
国家自然科学基金资助项目(61070162)
河南省科技攻关计划项目(122102210258)
关键词
风险预警
煤
瓦斯
单一阀值
增益决策树
Risk early warning
Coal
The gas
A single threshold
Gain the decision tree
