| Summary: | On the basis of the water inrush theory of coal mines and analysis of field measured data, this paper established water influx indicators for water inrush from coal seam floor. Through the feature selection of the Wrapper evaluation strategy, the main control factors affecting the water inrush of coal mine were finally selected. After training and establishing a dynamic gated recurrent unit (GRU) neural network prediction model of water inrush in coal seam, this model was compared with other static prediction models. The accuracy predicted by gate recurrent unit neural network model during the validation, training, and test phases was higher than that obtained with other static models, indicating that gate recurrent unit model can well predict the water inrush from coal seam floor and improve coal mine production safety.
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