Research on the prediction model of gas emission based on grey system theory - Liyang Bai; Hui Geng; Guangming Yu (Scientific Reports)
Abstract Accurate prediction of the gas emission volume in the mining face can prevent gas accidents in advance, optimize the mining plan, reduce energy consumption, and contribute to the safe, efficient and green development of coal mines. In order to improve the prediction accuracy of gas emission volume.A prediction model of gas emission based on grey system theory is proposed.11 indexes such as gas content, coal seam depth, coal seam thickness, coal seam dip angle and inclined length of working face are selected as the influencing factors of gas emission.The weight of each factor is determined by grey correlation analysis. The related factors with a grey correlation degree greater than 0.7, from largest to smallest, are: coal seam gas content X1 > coal seam thickness X3 > mining intensity X11 > coal seam depth X2 > adjacent gas content X8.Combined with the field measured data, three grey prediction models for predicting gas emission are determined.After a posterior difference test, the accuracy of GM (0,12) model is excellent.By comparing the predicted data of the model with the actual data, it shows that the GM (0,N) model has good forecasting results.At the same time, in order to prove the advantages of GM (0,N) model, the prediction results are compared with those of multiple linear regression model.The prediction results of GM (0,N) model and multiple linear regression model are compared.The prediction results show that the relative error of GM (0,12) model is 0.799%,the relative error of multiple linear regression model is 3.643%.It shows that GM (0,12) model can better predict gas emission.