ROCKBURST TENDENCY PREDICTION BASED ON AHP-TOPSIS EVALUATION MODEL
GONG Jian,HU Nailian,CUI Xiang,WANG Xiaodong
(State Key Laboratory of High-efficient Mining and Safety of Metal Mines,Ministry of Education,University of Science and Technology Beijing,Beijing 100083,China)
Abstract:A comprehensive model of evaluating the prediction of rockburst was established based on the analytic hierarchy process(AHP) and the technique for order preference by similarity to ideal solution(TOPSIS). The indices of evaluation of rockburst were selected from lithological,stress and rock conditions. The criterion of rockburst level was constructed according to the critical values of evaluation indices. The weight matrix of the evaluation indices was determined objectively according to the AHP and the degree of closeness was analyzed with the TOPSIS,as such the prediction level of rockburst was determined. The results of a case study show that the predicted results of rockburst based on the evaluation model of AHP-TOPSIS are consistent with the actual measured results and agree well with the outcomes from the method of fuzzy mathematics. The proposed method considers various inducing factors of rockburst and avoids the limitation of a single criterion. The importances of various factors are compared to make the predicted results more sensible.
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