An improved BP neural network algorithm for prediction of roadway support

Based on the engineering practice and the research and analysis of the knowledge in the field of roadway support, the paper puts forward to use an improved BP neural network to study the supporting types by the investigation, and obtained the related factors of the supporting types of the mining roadway and the successful reinforcement cases of the roadway. The proposed algorithm is applied to the prediction of coal roadway support parameters, and the main influencing factors of coal roadway support design are determined. From the typical engineering cases of roadway support collected on site as neural network training samples, the forecasting model of support parameters is established. Through the experimental data and simulation results, it can be seen that both the error convergence process and results of convergence speed, convergence accuracy and support types are ideal, the prediction error is within the allowable range, and the prediction accuracy is high, which verifies the reliability of this method and provides a new research idea and good application value for the study of support types of mining roadway. © 2021, North Atlantic University Union NAUN. All rights reserved.