Application of the prediction for mine floor water inrush quantity based on FOA-SVR model

Mine water inrush is a common mine disaster which is sudden and intense.In order to better prevent mine floods and reduce material losses and casualties caused by disasters, a prediction model for mine floor water inrush quantity is built by studying the principle and characteristics of FOA-SVR model, using the fruit fly algorithm (FOA) to optimize support vector regression algorithm (SVR) to select the excellent model parameters.For the nonlinear, small sample problem of floor water inrush, water pressure, aquifer thickness, aquiclude thickness, height of water flowing fractured and fault throw are selected as the characteristic factors.After the SVR parameters are optimized by the fruit fly algorithm, the FOA-SVR prediction model for floor water inrush quantity is built, and the output is the water inrush quantity that we need to predict.Comparing the predicted results of FOA-SVR model with the predicted results of SVR model, the results show that, the model is more accurate than the SVR model in the accuracy of predicting water inrush quantity and has certain application value.