摘要
在简要阐述了神经网络BP模型及其反传算法一般原理的基础上 ,基于工程实例 ,建立了堆石坝料开采爆破块度预测的神经网络BP模型 ,并将网络预测值与R—R、G—G—S分布模型拟合值进行了比较 。
The general principles of neural network and the back propagation algorithm were discussed in this paper. Based on the experiments of engineering blasting, a neural network model for prediction of rock fragmentation in rock-fill material by blasting is established. The values predicted by the network are compared with R-R and G-G-S experimental model of fragmentation. The results show that the neural network model is reliable.
