Application of RAGA-PPC cloud model in slope stability evaluation

doi:10.16265/j.cnki.issn1003-3033.2019.09.009

Abstract

Abstract: In order to accurately evaluate slope stability of open pits and prevent slope accidents, firstly, six indexes, including cohesion, slope angle, slope height, pore water pressure ratio and natural bulk density, were selected to establish a slope stability evaluation index system. Secondly, based on 20 sets of samples, PPC method was adopted to project multidimensional data on one-dimensional plane, and weight values of each index were calculated with RAGA optimized projection indexes. Then, membership degree of each stability level were obtained by using forward cloud generator, on the basis of which weighted membership degree of slope stability levels was calculated. Finally, a RAGA-PPC evaluation cloud model combining qualitative and quantitative analysis was constructed and verified through 5 groups of samples. The results show that the most important factor that affects slope stability is slope height. RAGA-PPC cloud model's accuracy rate for evaluating 20 sets of sample data is 95.0% and 100% for 5 sets of sample data.

Key words: open pit slope, real-coded accelerated genetic algorithm (RAGA), stability evaluation, cloud model, projection pursuit classification (PPC)

CLC Number:

X913.4

WU Menglong, YE Yicheng, HU Nanyan, YAO Nan, JIANG Huimin, LI Wen. Application of RAGA-PPC cloud model in slope stability evaluation[J]. China Safety Science Journal, 2019, 29(9): 57-63.

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