Prediction of water inrush from floor based on GWO-Elman neural network

China is the world’ s largest coal producer and consumer,especially in the North China region of China,where coal reserves are very rich. However,due to the complex hydrogeological conditions in North China,accidents occur frequently during the actual coal production,especially water inrush accidents in coal floor,which often result in serious casualties and coal losses. Therefore,the prediction of coal floor water inrush has become the focus of research in the field of coal mine safe production. Hongqi Coal Mine of Juye Coalfield is a typical North China coal field. Its main recoverable coal seam is No. 3 coal seam,with an average thickness of 5. 48 m. The coal seam is seriously threatened by floor water inrush in the actual production process,and some floor water inrush accidents have occurred many times during mine construction and production. In order to predict the water inrush from the bottom of the No. 3 coal seam,based on the analysis and collection of relevant hydrogeological data of the Hongqi coal mine,seven factors are selected,including the fractal dimension of the fracture,the heart rate,the thickness of the water barrier,the amount of water inflow,the permeability coefficient,the total thickness of the aquifer of the floor,and the water pressure of the confined aquifer,these seven factors are used as the main influencing factors for the prediction of water inrush from the floor. Taking the actual field data as input samples,the best weights and thresholds of Elman neural network optimization are obtained by Grey Wolf Optimizer (GWO),which are 18. 748 2 and 0. 014 435,respectively. Then the corresponding GWO-Elman neural network prediction model for floor water inrush is established. On this basis,the test sample input model is verified,and the accuracy rate is 100% . The entropy method is used to determine the weight of the vulnerability index method for comparison. The neural network model is more accurate and can be used in engineering practice. Finally,the established neural network model is used to predict the water inrush from the floor of the two unmined working faces,and the prediction results will guide the actual safety production of the mine.