Optimization model of unascertained measurement for underground mining method selection and its application

Abstract

An optimization model of underground mining method selection was established on the basis of the unascertained measurement theory. Considering the geologic conditions, technology, economy and safety production, ten main factors influencing the selection of mining method were taken into account, and the comprehensive evaluation index system of mining method selection was constructed. The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively. New measurement standards were constructed. Then, the unascertained measurement function of each evaluation index was established. The index weights of the factors were calculated by entropy theory, and credible degree recognition criteria were established according to the unascertained measurement theory. The results of mining method evaluation were obtained using the credible degree criteria, thus the best underground mining method was determined. Furthermore, this model was employed for the comprehensive evaluation and selection of the chosen standard mining methods in Xinli Gold Mine in Sanshandao of China. The results show that the relative superiority degrees of mining methods can be calculated using the unascertained measurement optimization model, so the optimal method can be easily determined. Meanwhile, the proposed method can take into account large amount of uncertain information in mining method selection, which can provide an effective way for selecting the optimal underground mining method.