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矿井涌水水源的主成分分析和BP神经网络判别

Wenfei CHEN,Qimeng LIU,Yu LIU,Zhouyang JIN,Wentao ZHANG

Journal of Heilongjiang University of Science and Technology（2014）

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Abstract
为准确判别矿井涌水水源,针对矿井各主要含水层的水化学特征数据样本,利用主成分分析法消除变量中的重复信息,采用BP算法对网络进行训练,实现对随机挑选样本的判别,并与Bayes判别结果进行比较.结果表明:主成分分析与BP神经网络相结合的方法判别涌水水源的正确率为82.35％,优于Bayes判别法.该研究为有效开展矿井防治水工作提供了参考.
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Key words
discrimination of water source,principal component analysis,BP neural network
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