An intelligent water source discrimination method for water inrushes from coal seam roofs in the Inner Mongolia-Shaanxi border region
Water hazard on the coal seam proof induced by high-intensity coal mining are increasingly prominent in the Inner Mongolia-Shaanxi border region.The effective,accurate water-source discrimination of the water inrushes is the key to water hazard prevention.This study investigated three typical mines in the Inner Mongolia-Shaanxi border region.To this end,principal component analysis(PCA)was employed to extract principal components from 80 groups of groundwater samples.Then,with inorganic indicators K++Na+,Ca2+,Mg2+,Cl-,SO4 2-,HCO3-and TDS and organic in-dicators UV254,TOC,and dissolved organic matter(DOM)'s fluorescence spectra as discriminant indicators,this study proposed a intelligent identificaton method of PCA-AFSA-RF roof water inrush source by using artificial fish swarm al-gorithm(AFSA)to improve random forest(RF).First,a PCA-RF discriminant model was established,with accuracy(Ac),precision(Pr),recall(Rc),and F-measure(f1)of 83.00%,83.17%,80.42%,and 79.57%,respectively.Then,in the PCA-RF discriminant model,AFSA was employed to optimize the number of decision trees,the depth of trees,and the minimum sample number needed for internal node splitting.Furthermore,a genetic mechanism was introduced into AF-SA to avoid local optimization.In this way,a PCA-AFSA-RF water-source discriminant model for water inrushes on coal seam roofs was established,with Ac,Pr,Rc,and f1 of up to 92.18%,91.11%,87.58%,and 88.82%,respectively,in-creasing by 9.18%,7.94%,7.16%,and 9.25%compared to the PCA-RF model.Furthermore,the PCA-AFSA-RF exhib-ited a back substitution accuracy reaching 97.50%.Finally,this model was used for the water-source discrimination of 12 water samples from the mines,yielding results consistent with the actual results in the field.This indicates that the PCA-RF model with improved AFSA enjoys better accuracy and generalization ability.The research results of this study can provide a new method for the accurate water-source identification of water inrushes from coal seam roofs.
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