Identification of mine water inrush source based on combinationweight-theory of improved grey relational degree

Based on combination weights and improved grey relational theory, a model for identifying water sources of mine water inrush was established for 35 learning samples extracted from 4 aquifers in Panxie Mining Area, and the model was used to identify water sources for 7 test samples. The results show the content changes of six chemical index values, such as Na++K+, Ca2+, Mg2+, Cl-, SO2-4 and HCO-3 in the learning samples and test samples of the same aquifer are more similar, which conforms to the grey relational theory. The combined weight comprehensively considers the subjective and objective weights, avoids the interference of human factors, and considers the actual situation of the identification indicators. Among the six identification factors calculated by the combined weight method, the weights of Ca2+, Mg2+ and HCO-3 are 0.231, 0.383 and 0.203, respectively, and the combined weight values of the three factors account for 81.7% of the total value, indicating that these three indicators have a great impact on the identification result of mine inrush water source. The established combination weight-improved grey relational degree model was used to identify the test water samples of 7 different aquifers. Except for one water sample, the others were consistent with the actual results, and the recognition accuracy rate reached 86%, indicating that the model has certain accuracy and applicability in mine water source identification.