基于组合预测与变精度粗糙模糊集的采空区稳定性评价

doi:10.11872/j.issn.1005-2518.2017.03.098

Abstract

Abstract:

In order to accurately evaluate stability of mine goafs and analyze its main influential factors，according to the preliminary test data of goafs roof subsidence displacement，combination forecasting was applied to compose final predictive values of roof subsidence displacement by vary models，and then goafs stability was judged by resultant predictive values.Goafs stability was set as decision attribute，and its influential factors were set as condition attributes，variable precision rough fuzzy set was applied to probabilistically decision analyze assessment knowledge system of goafs stability，and 13 β- decision rules which β was 70% were got. It shows that goaf area，crustal stress size and temporary support way are decisive factors to goafs stability，and the classification quality of probabilistic decision rules is 62.96%，it is high，which can be references for stability judge and its law analysis.

Key words: goaf, stability evaluation, combined forecasting, BP neural network, membership function, mathematical model, rough set, fuzzy comprehensive evaluation method

CLC Number:

TD325

DENG Gao，YANG Shan. Stability Evaluation of Goafs Based on Combined Forecasting and Variable Precision Rough Fuzzy Set[J].Gold Science and Technology, 2017, 25(3): 98-107.

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Stability Evaluation of Goafs Based on Combined Forecasting and Variable Precision Rough Fuzzy Set

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