灰色系统和BP神经网络相结合的矿产资源预测模型

THE MINERAL RESOURCES FORECAST MODELS BY COMBINING GREY SYSTEM AND THE BP NEURAL NETWORKS

这里介绍了灰色系统和BP神经网络相结合的预测原理,利用BP网络,对改进的GM(1,1)残差修正模型所得预测的结果进行再预测的组合预测模型,并对攀枝花市钒钛磁铁矿的产量进行了预测。计算结果表明,该预测方法是可靠的,并具有较高的预测精度。

This article introduces the forecast principle by combining the grey system and the BP neural networks.The BP neural networks are used to improve remnant error model of GM(1,1) obtained forecast result carried on the combining forecast model which forecast again and has carried on the forecast to the vanadium titanomagnetite output of Pan zhihua.The computed result indicated that this forecast method is reliable,and has high forecast precision.