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首页> 外文会议>International Conference on Machinery, Materials Science and Energy Engineering >Research on Forecasting Model of Gas Emission in Coal Mining and Heading Face Based on ARIMA-GM Method
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Research on Forecasting Model of Gas Emission in Coal Mining and Heading Face Based on ARIMA-GM Method

机译：基于ARIMA-GM方法的煤矿煤矿煤矿煤气排放预测模型研究

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摘要

In order to achieve the accurate forecasting of dynamic gas emission in coal mining and heading working face, firstly, this paper utilizes grey model GM (1,1) and Autoregressive Integrated Moving Average Model (ARIMA) to forecast the concentration of gas emission respectively based on the time series, and then a new combination forecasting model, ARIMA-GM, built by the method of variance reciprocal weighting is represented to forecast and analyze the concentration of gas emission, finally, the gas pre-warning is obtained according to forecasting results. An application example of forecasting in 10502 heading working face of Xin Xing coal mine is presented and its results show that the combination forecasting model of ARIMA and GM provides a better fitting effect and a higher forecasting accuracy, and which has certain general employing, in addition, its guiding significance to the safe mining and heading of coal mine are determined.
机译：为了实现准确的煤炭开采动态气体排放的预测，首先，本文利用灰色模型GM（1,1）和自回归综合移动平均模型（ARIMA），以分别基于基于气体发射的浓度在时间序列中，然后通过方差往复方式构建的新组合预测模型ARIMA-GM表示，以预测和分析气体排放浓度，最后，根据预测结果获得气体预警。提出了鑫兴煤矿10502档工作面预测的应用示例及其结果表明，Arima和GM的组合预测模型提供了更好的拟合效果和更高的预测精度，并且具有一定的普通雇用，另外，确定了对安全采矿和煤矿标题的指导意义。

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