Research on Prediction Accuracy of Coal Mine Gas Emission Based on Grey Prediction Model

被引:11
|
作者
Zeng, Jun [1 ]
Li, Qinsheng [2 ]
机构
[1] Shandong Vocat & Tech Univ Int Studies, Sci Res Off, Rizhao 276826, Peoples R China
[2] Shandong Univ Sci & Technol, Coll Min & Safety Engn, Qingdao 266590, Peoples R China
基金
中国国家自然科学基金;
关键词
grey prediction model; coal mine safety management; coal mining; gas emission from working face; grey prediction error analysis; BP NEURAL-NETWORK; HAZARD EVALUATION; GRAY MODEL; OUTBURST;
D O I
10.3390/pr9071147
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
In order to achieve the accuracy of gas emission prediction for different workplaces in coal mines, three coal mining workings and four intake and return air roadway of working face in Nantun coal mine were selected for the study. A prediction model of gas emission volume based on the grey prediction model GM (1,1) was established. By comparing the predicted and actual values of gas emission rate at different working face locations, the prediction error of the gray prediction model was calculated, and the applicability and accuracy of the gray prediction method in the prediction of gas gushing out from working faces in coal mines were determined. The results show that the maximum error between the predicted and actual measured values of the gray model is 2.41%, and the minimum value is only 0.07%. There is no significant prediction error over a larger time scale; the overall prediction accuracy is high. It achieves the purpose of accurately predicting the amount of gas gushing from the working face within a short period of time. Consequently, the grey prediction model is of great significance in ensuring the safety production of coal mine working face and promote the safety management of coal mine.
引用
收藏
页数:13
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