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CHEN Juntao,LI Wenxin,XUE Feng,et al. Comprehensive evaluation of TOPSIS-RSR grouting effect based on subjective and objective combined weights[J]. Coal Science and Technology,2023,51(S2):1−9. doi: 10.13199/j.cnki.cst.2022-1695
Citation: CHEN Juntao,LI Wenxin,XUE Feng,et al. Comprehensive evaluation of TOPSIS-RSR grouting effect based on subjective and objective combined weights[J]. Coal Science and Technology,2023,51(S2):1−9. doi: 10.13199/j.cnki.cst.2022-1695

Comprehensive evaluation of TOPSIS-RSR grouting effect based on subjective and objective combined weights

  • The evaluation of grouting effect is one of the crucial links in grouting water control project. As grouting technology matures, traditional methods of evaluating grouting effects are more subjective and fewer objective, which leads to the drawback that the evaluation results deviate from reality. Taking the grouting project of 8901 working face in Baizhuang Coal Mine of Shandong Province as the background, combining existing research and field experience, the grouting final pressure, permeability coefficient, water absorption rate and the number of dry material per ton of water are selected as the evaluation indexes, and the comprehensive evaluation system of grouting effect is established. Based on the comprehensive evaluation theory, a comprehensive subjective and objective weighting method is proposed, which based on analytic hierarchy process(AHP) combined with CRITIC objective weighting method. And the objectivity ofpf indicator assignment is improved by combining subjective and objective weights. Based on the combination weighting method, a comprehensive evaluation model of grouting effect is established, which is sorted by technique for order preference by similarity to an ideal solution (TOPSIS) and assisted by rank sum ratio (RSR). The evaluation results are converted into visual partition maps and compared with the actual evaluation results of field engineering and the results of the testing process after grouting, and the results show that the model has superior accuracy and rationality.
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