Research on Rockburst Risk Level Prediction Method Based on LightGBM−TCN−RF

Rockburst hazards pose a severe threat to mine safety. To accurately predict the risk level of rockburst, a LightGBM−TCN−RF prediction model is proposed in this paper. The correlation coefficient heat map combined with the LightGBM feature selection algorithm is used to screen the rockburst characte...

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Autors principals:	Li Ma, Jiajun Cai, Xinguan Dai, Ronghao Jia
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2022-08-01
Col·lecció:	Applied Sciences
Matèries:	rockburst risk level monitoring and warning LightGBM−TCN−RF model timing model
Accés en línia:	https://www.mdpi.com/2076-3417/12/16/8226
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