Prediction of Gas Concentration Based on LSTM-LightGBM Variable Weight Combination Model

Gas accidents threaten the safety of underground coal mining, which are always accompanied by abnormal gas concentration trend. The purpose of this paper is to improve the prediction accuracy of gas concentration so as to prevent gas accidents and improve the level of coal mine safety management. Co...

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Veröffentlicht in:	Energies (Basel) Jg. 15; H. 3; S. 827
Hauptverfasser:	Wang, Xiangqian, Xu, Ningke, Meng, Xiangrui, Chang, Haoqian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.02.2022
Schlagworte:	Accuracy Algorithms coal mine safety Coal mining Correlation analysis Data collection Datasets Feature selection gas concentration prediction LightGBM LSTM LSTM-LightGBM variable weight combination Machine learning Neural networks Time series China
ISSN:	1996-1073, 1996-1073
Online-Zugang:	Volltext
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