TITLE:
Identification of Mine Water Inrush Source Based on PCA-BP Neural Network
AUTHORS:
Mingcheng Ning, Haifeng Lu
KEYWORDS:
Mine Water Inrush, Analysis of Hydrochemical Characteristics, Principal Component Analysis (PCA), Back Propagation Neural Networks, Water Source Identification
JOURNAL NAME:
International Journal of Geosciences,
Vol.14 No.8,
August
17,
2023
ABSTRACT: It is of great significance
to analyze the chemical indexes of mine water and develop a rapid
identification system of water source, which can quickly and accurately
distinguish the causes of water inrush and identify the source of water inrush,
so as to reduce casualties and economic losses and prevent and control water
inrush disasters. Taking Ca2+, Mg2+, Na+ + K+, , , Cl-, pH value and TDS as discriminant indexes,
the principal component analysis method was used to reduce the dimension of
data, and the identification model of mine water inrush source based on PCA-BP
neural network was established. 96 sets of data of different aquifers in Panxie
mining area were selected for prediction analysis, and 20 sets of randomly
selected data were tested, with an accuracy rate of 95%. The model can
effectively reduce data redundancy, has a high recognition rate, and can
accurately and quickly identify the water source of mine water inrush.