Research on Prediction Model of Explosive Explosion Velocity Based on Improved BP Neural Network

Abstract

In order to improve the feasibility and accuracy of explosive speed prediction, a combination of factor analysis and BP neural network method is proposed to propose an improved BP neural network prediction method. According to the raw data of the main influencing factors related to the explosion speed of explosives, the factor analysis method was used to process the dimensional data of the factors affecting the explosive speed of 20 explosives, and three common factors were obtained. The explosion rate of the original 13 explosives was replaced by three common factors. Influencing factors are used as the input layer parameters of BP neural network. The explosive explosion velocity prediction model combined with factor analysis and BP neural network method is established to predict the explosion velocity of explosives. The improved BP neural network prediction method is verified by the example data. The final verification result is that the relative average error between the predicted and actual values of the 15 training samples is 1.05%, which proves that the improved BP neural network model with training has a good fitting effect. The relative errors of the five predicted samples were 1.44%, 2.14%, 3.49%, 0.78%, and 1.95%, respectively, which were less than 10%, which proved that the improved BP neural network prediction model has better prediction accuracy.