摘要
将灰关联理论运用到影响矿井瓦斯涌出量预测指标的选取中,确定了影响矿井瓦斯涌出量预测的主要指标。根据这些指标建立了矿井瓦斯涌出量的BP神经网络模型,结合某矿的实际数据,对预测模型进行训练和验证,得到了很高的预测精度和较快的收敛速度,取得了较好的实际应用效果。
The paper associated Grey relation to select the main prediction indexs which influence the gas disaster. Based on these indexs we presented a BP neural network model to forecast mine gas disaster. And the model was trained and tested with experimental dat in a certain coal mine, and achieved good results in practical applications with high accuracy and faster convergence rate.
出处
《煤》
2009年第4期21-24,共4页
Coal
关键词
瓦斯涌出量
预测指标
灰关联
BP神经网络
gas emission quantity
prediction index
grey relation
BP neural network
