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Study on influencing factors of gas emission in mining face based on regression shapley value decomposition method

Tao YANG ; Ziqi XIE ; Jingyan HU ; Chen WANG

Mei kuang an quan, 2023-11, Vol.54 (11), p.18-24 [Periódico revisado por pares]

Editorial Office of Safety in Coal Mines

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  • Título:
    Study on influencing factors of gas emission in mining face based on regression shapley value decomposition method
  • Autor: Tao YANG ; Ziqi XIE ; Jingyan HU ; Chen WANG
  • Assuntos: gas gushing from mining face ; regression model ; shapley value decomposition ; spss statistical analysis software ; stata statistical analysis software
  • É parte de: Mei kuang an quan, 2023-11, Vol.54 (11), p.18-24
  • Descrição: With the increasing of mining depth, the underground environment becomes more complex and so it is urgent to determine the influence degree of various factors on the change of gas emission in the mining face. The Shapley value decomposition method, based on regression, was used to determine the contribution of each factor to the amount of gas gushing from the recovery workings. SPSS statistical analysis software was used to analyze the data to ensure that the obtained data met the prerequisite of applying multiple linear regression analysis; through stata statistical analysis software, OLS regression method was used to model the modified data and establish the regression equation. Based on the Shapley value decomposition method, the regression equation is decomposed, and the decomposition results are verified by the verification group data. On the premise that the occurrence condition of coal seam is super thick coal seam and the quaternary stratum is mainly loess, it is concluded that the contribution rate o
  • Editor: Editorial Office of Safety in Coal Mines
  • Idioma: Chinês
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