光面爆破效果BP神经网络预测

介绍了BP神经网络的基本原理，基于Matlab工具箱建立了预测光面爆破效果神经网络模型，从岩石力学性质，周边爆破参数两个方面对光面爆破效果进行分析和预测。为了加快神经网络模型的收敛速度。增强其跳出局部极小点的能力，采用了附加动量法和自适应学习速率结合的方法对网络进行训练，利用该模型对光爆效果进行了预测。取得了很好的效果。

Study on forecasting smooth-surface blasting effects based on BP neural network

This paper introduces the basic principle of BP neural network and establishes a modal of the forecasting smooth-surface blasting effects based on tools box of Matlab. The modal analyzes and predicts the relationship among rock mechanics prosperities, blasting parameters and smooth-surface blasting effects. In order to speed up the convergence speed of the neural network model and avoid it falling into a local minimum point, the additional momentum and adaptive learning rate method is adopted. This modal is used and gets goods effects.