HAN Z, WANG X L, SHI L Q.Study on application of PCA-BP neural network in discrimination of karst water inrush source in mine[J].Journal of Henan Polytechnic University(Natural Science) ,2023,42(1):46-53.

doi:10.16186/j.cnki.1673-9787.2020070099

Received:2020/07/09

Revised:2021/12/27

Published:2023/01/25

Study on application of PCA-BP neural network in discrimination of karst water inrush source in mine

HAN Zhong1, WANG Xiaoli2, SHI Longqing2

1.No.6 Institution of Geology and Mineral Resources of Shandong Province，Weihai  264209，Shandong，China；2.College of Geosciences and Engineering，Shandong University of Science and Technology，Qingdao  266590，Shandong，China

Abstract:The water quality of Ordovician limestone and Xujiazhuang limestone in Feicheng Coalfield is very similar，so that it is difficult to discriminate the source of water inrush.In order to solve this problem，five trace elements including F，Br，I，H₃BO₃ and Rn were selected as discriminant indexes.SPSS software was used to model principal component analysis，the PCA-BP neural network model was established by substituting the principal components into MATLAB software.In terms of convergence process and output accuracy，PCA-BP neural network model was compared with BP neural network model，system clustering analysis discriminant model and Fisher discriminant analysis model.The results showed that the accuracy of PCA-BP neural network model was 100%，it hasd the advantages of the highest output accuracy，the smallest error，the fast convergence speed and the few iterations.Therefore，the model had a certain application value for discriminating similar limestone water inrush sources.

Key words:Feicheng coalfield;water inrush source;PCA-BP neural network;Ordovician limestone;Xujiazhuang limestone;discriminant accuracy

 PCA-BP神经网络在矿山...溶突水水源判别中的应用研究_韩忠.pdf