Abstract: The blasting effect is not ideal in Majiata open-pit mine, such as higher rate of blocky ore, high explosives consumption, and abundant residuals.To solve these problems, an optimization model of the open-pit mine blasting parameters based on BP neural network is built.The actual blasting parameters are applied into the model as the sample data.The tests with practical data show that the model has higher prediction accuracy.With the on-site tests and model simulation analysis, a good blasting result is obtained by using the optimized parameters.Large block rate is controlled below 2%, explosives consumption reduced from 0.41 kg/m³ to 0.37 kg/m³, blasting volume of each hole increased from 17 m³/m to 23 m³/m.

Key words: Blasting parameters optimization, Neural network, Open-pit mine