Application of BP neural network discriminant model in prediction of water inrush source in Zhongguan iron mine
Zhongguan Iron Mine is a typical large water deposit in China,and its groundwater system is relatively com-plex.In order to ensure the safety of life and property of workers,it is necessary to analyze and accurately predict the source of water inrush in the process of mine production in time.Based on the water quality test results of water samples collected from the existing water outlet points at three mining levels in Zhongguan Iron Mine,the water quality characteristics of Zhongguan I-ron Mine area are analyzed,and the BP neural network discriminant model is used to establish the mine water source discrimi-nant model.According to the data analysis of the test results,the BP neural network discriminant model has a correct rate of 100%for Ordovician limestone water and diorite fissure water,and a correct rate of 80%for mixed water.The BP neural net-work discriminant model has high accuracy in the prediction of water inrush source in Zhongguan Iron Mine,which provides a theoretical basis for water prevention and control.
BP neural network discriminant modelgroundwaterwater inrush source discriminationZhongguan iron mine
NETL
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