| Citation: | Bocheng Zhang, Huiming Tang, Yibing Ning, Kun Fang, Ding Xia. Weight Analysis of Impact Factors of Interbedded Anti-Inclined Slopes Block-Flexure Toppling Based on Support Vector Regression. Journal of Earth Science, 2024, 35(2): 568-582. doi: 10.1007/s12583-023-1835-1
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Block-flexure toppling failure is frequently encountered in interbedded anti-inclined rock (IAR) slopes, and seriously threatens the construction of hydropower infrastructure. In this study, we first investigated the Lean Reservoir area's geological setting and the Linda landslide's characteristics. Then, uniform design and random design were used to design 110 training datasets and 31 testing datasets, respectively. Afterwards, the toppling response was obtained by using the discrete element code. Finally, support vector regression was used to obtain the influence weights of 21 impact factors. The results show that the influence weight of the slope angle and rock formation dip angle on the toppling deformation among tertiary impact factors is 25.96% and 17.28%, respectively, which are much greater than the other 19 impact factors within the research range. For the primary impact factors, the influence weight is sorted from large to small as slope geometry parameters, joints parameters, and rock mechanics parameters. Joints parameters, especially the geometric parameters, cannot be ignored when evaluating the stability of IAR slopes. Through numerical simulation, it was qualitatively determined that failure surfaces of slopes were controlled by cross joints and that the rocks in the slope toe play a role in preventing slope deformation.
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