基于BP神经网络的巷道围岩稳定性分级识别

Identify the stability classification of the surrounding rock through BP neural network in the mine tunnel

矿山围岩稳定性分级是矿山工程的基本参数,为矿山支护设计提供基础数据,利用BP神经网络进行围岩稳定性分级识别,有利于真实地刻画矿山围岩稳定性分级与其影响因素之间的非线性关系。本文研究了BP神经网络的工作原理及其改进,分析了某矿巷道围岩稳定性影响因素,确定建立了围岩稳定性分级的神经网络识别模型,并利用该模型对某矿山围岩分级进行了拟合,取得了很好的效果。

To the stability classification of the surrounding rock, it is base parameter to the designing support in the mine. It is avail to reflect the in-linear relation between the stability classification and the influent factor, using the BP neural network model. In this paper, studied the work principia and the modiled method of the BP neural network, the influence factors are analyzed to confirm the index of classification. The model of the BP （modified BP） neural network has built to identify the classified results, the model has been used in the mine tunnel, tha simulate results and the facts are very approximate.