Mine water inflow prediction model based on variational mode decomposition and gated recurrent units optimized by improved chimp optimization algorithm.

Water damage accidents occur frequently in mines in China, and accurate prediction of incoming water has become an important guarantee for the safe and efficient mining of coal resources. To improve the accuracy of mine water prediction, this paper proposes the VMD-iCHOA-GRU mine water prediction model by selecting and improving it according to the previous research results in decomposition method, time series prediction model and optimization algorithm. After processing the raw data and setting the model parameters, MAE, RMSE, MAPE and R are selected as the evaluation indexes of prediction accuracy, and VMD-GRU model, iCHOA-GRU model, CHOA-GRU model and GRU model are selected as the comparison models to validate the advantages of the VMD-iCHOA-GRU model in the prediction of mine inrush water. The results show that the VMD-iCHOA-GRU model has the best prediction effect on the trend of water inflow, with the evaluation index values of 0.00862, 0.01059, 0.02189%, 0.87079, respectively, and with the smallest MAE, RMSE, MAPE, and the largest R, and the highest prediction accuracy of the VMD-iCHOA-GRU model.