• 标题：Discriminant analysis of mine water inrush sources with multi-aquifer based on multivariate statistical analysis
• 关键词：Mine inrush water; Ion contents; Multicollinearity; Correlation; Fuzzy cluster analysis; Factor analysis; Fisher discriminant model
• 作者：

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Accurate and effective identification of the source mine water inrush water is vital for warning system implementation and post-disaster rescue decision-making and is crucial for mine water disaster prevention plans. To fully excavate the hydrogeological information carried by the water samples of different water sources, and fully consider the influence of the correlation between the ions and the existence of multi-collinearity on the discrimination results, so as to improve the accuracy of the inrush water source discrimination, this study conducted multivariate statistical analysis and discriminant analysis on 37 water samples of three types of water sources in Xutuan coal mine, and established the Fisher discriminant model for mine water inrush sources based on fuzzy cluster analysis and factor analysis. The discriminant accuracy of the model was tested using re-substitution and cross-validation, and compared with the discriminant result of traditional Fisher discriminant model. The results showed that the discriminant accuracies of the re-substitution and cross-validation were 91.9% and 89.2%, respectively, while the discrimination accuracy of cross-validation of the traditional Fisher discrimination model was 86.5%. The discrimination accuracy of this model was higher than that of the traditional Fisher discrimination model. Therefore, the Fisher discriminant model for mine water inrush sources based on fuzzy cluster analysis and factor analysis established in this study can improve the accuracy of a water source discrimination model, and can provide a useful reference for mine water disaster prevention.