矿井涌水水源的主成分分析和BP神经网络判别
Journal of Heilongjiang University of Science and Technology(2014)
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.
MoreKey words
discrimination of water source,principal component analysis,BP neural network
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined