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Volume 7 Issue 4
Dec.  2019
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Article Contents
YANG Liu, WEN Xue-ru, WU Xiao-li, et al. 2019: Height prediction of water flowing fractured zones based on BP artificial neural network. Journal of Groundwater Science and Engineering, 7(4): 354-359. doi: DOI: 10.19637/j.cnki.2305-7068.2019.04.006
Citation: YANG Liu, WEN Xue-ru, WU Xiao-li, et al. 2019: Height prediction of water flowing fractured zones based on BP artificial neural network. Journal of Groundwater Science and Engineering, 7(4): 354-359. doi: DOI: 10.19637/j.cnki.2305-7068.2019.04.006

Height prediction of water flowing fractured zones based on BP artificial neural network

doi: DOI: 10.19637/j.cnki.2305-7068.2019.04.006
  • Publish Date: 2019-12-28
  • Factures caused by deformation and destruction of bedrocks over coal seams can easily lead to water flooding (inrush) in mines, a threat to safety production. Fractures with high hydraulic conductivity are good watercourses as well as passages for inrush in mines and tunnels. An accurate height prediction of water flowing fractured zones is a key issue in today's mine water prevention and control. The theory of leveraging BP artificial neural network in height prediction of water flowing fractured zones is analysed and app-lied in Qianjiaying Mine as an example in this paper. Per the comparison with traditional calculation results, the BP artificial neural network better reflects the geological condi-tions of the research mine areas and produces more objective, accurate and reasonable results, which can be applied to predict the height of water flowing fractured zones.
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    LI Zhen-hua, XU Yan-chun, LI Long-fei, et al. 2015. Forecast of the height of water flowing fractured zone based on BP neural networks. Journal of Mining and Safety Engineering, 32(6): 905-910.
    XIE Xiao-feng, LI Xi-bing, SHANG Xue-yi, et al. 2017. Prediction of height of water flowing fractured zone based on PCA-BP neural networks model. China Safety Science Journal, 27(3):100-105.
    CHAI Hua-bin, ZHANG Jun-peng, YAN Chao. 2018. Prediction of water flowing height in fractured zone of overburden strata based on GA-SVR. Journal of Mining & Safety Engineering, 35(2): 359-365.
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