神经网络在矿井突水水源判别中的应用

详细信息

Application of Neural Network in Water Source Distinguishing of Mine Water Inrush

1.
Xiaoming Coal Mine of Tiefa Coal Industry (Group) Co., Ltd., Diaobingshan 112700, China. 2.School of Information and Electrical Engineering of CUMT., Xuzhou 221116, China

摘要: 提出了一种采用改进的SOM神经网络对矿井突水水源进行判别的方法。该方法把水质中的Na+、K+、Ca2+、Mg2+、Cl-、SO2-4和HCO-3等7种离子的含量作为判断因素，结合改进的SOM神经网络模型，对20个水源样品进行分类。实验结果表明，该方法的误判率为0，能够准确地判别矿井突水水源。
- 矿井突水 /
- 水源判别 /
- SOM神经网络 /
- BP神经网络
Abstract: The paper proposed a method of using improved SOM neural network to distinguish water source of mine water inrush. The method takes seven irons contents of Na+, K+, Ca2+, Mg2+, Cl-, SO2-4 and HCO-3 in water as distinguished factors and combines with improved SOM neural network model to classify 20 samples of water source. The experiment result showed that mistake rate of the method is 0 and can distinguish water source of mine water inrush accurately.
- mine water inrush, water source distinguishing, SOM neural network, BP neural network