摘要
瓦斯预测有助于减少煤矿瓦斯灾害损失,甚至可以完全避免严重事故或灾害的发生。使用时间序列分析法,建立瓦斯灾害预测的自回归滑动平均ARMA模型,用AIC信息量准则实现模型定阶,用最小二乘法确定模型中的未知参数。对于非平稳时间序列,经差分处理后得到平稳时间序列,再用ARMA模型进行预测。仿真结果表明建立的预测模型和数据处理方法能获得较准确的预测结果。
Prediction of gas helps to reduce the loss of coal mine gas disaster, or even completely avoid the occurrence of se- rious accidents or disasters.Using time series analysis method,establish auto-regressive moving average ARMA model of gas disaster prediction,realize the mode~ order by AIC information criterion,determine the unknown parameters in the mode/ by using the method of least squares.For the non-stationary time series,the differential treatment to be stationary time se- ries,and ARMA model to be used forecasting.
出处
《工业控制计算机》
2013年第9期49-50,共2页
Industrial Control Computer
基金
江西省教育厅科技项目(GJJ13398)
关键词
瓦斯灾害预测
时间序列
自回归滑动平均
gas disaster prediction,time series,autoregressive moving average
