Study on blasting effect prediction of open-pit mine based on RBF neural network

Open-pit mine blasting is a system engineering affected by many factors, and it is one of the important links of open-pit mining.Its blasting effect directly affects the completion of the follow-up process.Improving blasting technology and quality is of great significance to mine safety and production.In this paper, the main parameters affecting blasting effect are selected by random forest, and the comprehensive blasting effect is determined by fuzzy evaluation.The prediction model of blasting effect based on RBF neural network is established.The model is applied to mine blasting effect prediction.Eleven groups of data measured in the blasting site are used as training samples, and five groups of data are used as prediction samples to test.Compared with BP neural network, it is found that RBF neural network has better prediction performance and can be widely used in field practice.