Research on application of PCA-WNN model in predicting the development height of water-flowing fractured zones
QIU Mei
XU Gaorui
SONG Guangyao
SHI Longqing
Abstract：The water-flowing fractured zone serves as the primary pathway for roof water influx in coal mines.Accurate prediction of the development height of this zone is crucial for anticipating and mitigating roof water hazards.Given the intricacies of the water-flowing fractured zone and the interdependencies among predic-tive factors,we have combined practical coal production data with engineering geological theory.Five key factors were identified:mining height,inclined length of the working face,ratio coefficient of hard rock lithology,mining depth,and the coal seam dip angle.By combining Principal Component Analysis(PCA)and Wavelet Neural Network(WNN),correlations and redundant information among the main controlling factors were eliminated through PCA.The uncorrelated principal components were subsequently used as input factors for WNN to establish the PCA-WNN model for predicting the height of the water-flowing fractured zone.The results indicated that the PCA-WNN model effectively eliminated correlations among factors,resulting in higher pre-diction accuracy and stability compared to the conventional WNN model.The relative error ranged from-6.66％to 6.13％,with an average of 4.46％.The PCA-WNN model was applied to forecast the height of the water-flowing fractured zone in the No.1302N working face of the Xinjulong coal mine in Shandong Province,and the predictions were found to be reliable.Therefore,this study presents a viable method for predicting the height of the water-flowing fractured zone in coal seam roofs in coal mines.
Keywords：PCA-WNN modelheight of the water-flowing fractured zonecorrelation analysisprincipal component analysiswavelet neural network
Publication Date：2023-12-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 27-36 )