神经网络在矿井水源判别中的应用

Application of BP Neural Network in Evaluation of Water Source in Mine

矿井突水是威胁煤矿安全生产的最大隐患之一,准确判别矿井水源是矿井防治水的前提。介绍了BP神经网络模型及其具体算法,并将其运用到矿井水源判别中。利用BP算法对训练样本进行学习,确定判别模型,根据已训练好的神经网络对样本进行判别。结果表明,采用人工神经网络对矿井水源进行判别,能得到较好的结果。因此,BP神经网络是判别矿井水源的一种有效方法,从而为矿井水源判别开辟了一条新途径,具有广泛的应用前景。

Distinguishing the water source in mine precisely is the precondition of the water prevention and cure of mine, as the water - inrush from coal is one of the biggest hidden troubles in threatening the coal mining safety. This paper proposed the model of BP neural network and its idiographie arithmetic, then applied it into the discrimination of the water source in mine. The discrimination model is established from the training samples using BP algorithm, and then the samples is distinguished from the well - trained neural network. The result indicates that the applying of the BP neural network to distinguish the water source in mine produces a better effectiveness. Therefor, the BP neural network is a effective way and a new approch to distinguishing the water source in mine, the prospect of its application is wide.