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    Construction and application of optimized model for mine water inflow prediction based on neural network and ARIMA model by Xiaoyu Gong, Bo Li, Yu Yang, MengHua Li, Tao Li, Beibei Zhang, Lulin Zheng, Hongfei Duan, Pu Liu, Xin Hu, Xin Xiang, Xinju Zhou

    Published 2025-01-01
    “…In order to better predict the amount of water surging in mines and to provide an important basis for mine water damage prevention work, based on the time series data of mine water influx from January 2020 to February 2023 in Northern Guizhou Province Longfeng Coal Mine, the BP-ARIMA prediction model was established by combining the BP neural network model and ARIMA autoregressive sliding average model, It also predicted the mine influx for a total of 6 months from July 2022 to February 2023, and compared the prediction results with four models, namely, BP neural network model, ARIMA autoregressive sliding average model, traditional method of Large well method, and GM(1,1) grey model, and used the absolute relative error as the calculation of model accuracy. …”
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