基于模糊BP神经网络的地下金属矿山岩层移动范围研究

地下金属矿山岩层移动的的影响因素复杂多变，而且具有很大的模糊性，用其他方法来研究岩层移动范围存在很大的困难，本文提出采用模糊BP神经网络方法进行地下矿山岩层移动范围预测。结果表明，选取的各因素之间与岩层的移动之间存在着较强的非线性规律，学习结果与期望结果基本吻合，进而从理论上证明移动角的大小与选取因素有着密切的联系，可以预测由于开挖引起的岩层和地表移动范围问题。

THE RESEARCH OF STRATA MOVEMENT SCOPE BASED ON FUZZY BP NEURAL NETWORK IN UNDERGROUND METAL MINE

The influencing factors of strata movement in underground metal mine are not only complicated but also fuzzy to some great extent, and it is very difficult to predict the scope of strata movement with other methods. In this paper, the prediction method of strata movement in underground mine is put forward in which fuzzy neural network is applied. The results show that there is a strong nonlinear mapping between the select factors and strata movement angle, the anticipant and the actual output results are very similar. It is proved that the numerical value of movement angle has much in common with the select factors in theory. And the scope of strata and surface movement due to mining can be predicted.