BP neural network model on the forecast for blasting vibrating parameters in the course of hole-by-hole detonation

Abstract

According to the neural network theory, combined with the technical characteristics of the hole-by-hole detonation technology, a BP network model on the forecast for blasting vibration parameters was built. Taking the deep hole stair demolition in a mine as an experimental object and using the raw information and the blasting vibration monitoring data collected in the process of the hole-by-hole detonation, carried out some training and application work on the established BP network model through the Matlab software, and achieved good effect. Also computed the vibration parameter with the empirical formula and the BP network model separately. After comparing with the actual value, it is discovered that the forecasting result by the BP network model is close to the actual value.