Mine ventilation rate forecasting based on improved genetic algorithm and BP neural network
SU Yixin
GE Le
CHENG Shijia
Abstract：Accurate wind velocity forecasting plays an important role in guaranteeing safety of the mine.In order to improve the accuracy of wind velocity forecasting of mine ventilation,a method of mine ventilation prediction based on improved genetic algorithm and BP neural network was presented.Meanwhile,by using the forward neural network,the prediction model of mine ventilation was established.In the model,the ranking selection strategy combines with probability survival method is used instead of the traditional selection operator,which obtained an improved genetic algorithm.The improved genetic algorithm is used to search the optimal weights and thresholds of the network.Based on this,BP algorithm was used to find the local optimization and then obtained the weights and threshold value of network.Meanwhile,the data of mine are used as the experimental data to conduct simulation and prediction,and the prediction results are compared with the several models.The forecasting result shows that the model improves the prediction accuracy of mine ventilation velocity.
Keywords：mine ventilation speed predictiongenetic algorithmneural networkBP algorithm
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 20-25 )