Application of BP neural network to forecasting and analysis of coal mine underground water inflow
The problem of mine water inflow is affected by many factors,which is non-linear and highly complex.According to the influential factors of underground water inflow and the data of water inflow from 2014 to 2018 in Huangling No.1 Coal Mine,two different methods of input neuron are used to create the neural network prediction model.The model is trained with known data,and the model with better fitting accuracy is obtained.The model is used to predict the water inflow,and fi-nally compared with the actual value.The results show that the prediction accuracy of the two neural network models is good,but the prediction accuracy is different.In terms of accuracy,the model with water inflow impact factor as input neuron is lower than that with water inflow combination as input neuron in short period.In long period however,the model with wa-ter inflow impact factor as input neuron is higher than that with water inflow combination as input neuron regarding the accu-racy.
mine water inflowBP neural networkiterative trainingfitting accuracy:model prediction
国家科技期刊平台
NSTL
万方数据
维普
