SLOPE STABILITY ANALYSIS USING LEAST SQUARE SUPPORT VECTOR MACHINE OPTIMIZED WITH ANT COLONY ALGORITHM
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Graphical Abstract
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Abstract
The relationship between slope stability and influencing factors is complex and nonlinear. Support vector machine (SVM) is used to build the nonlinear relationship. The parameters of SVM are optimized with a continuous ant colony algorithm (CACA). Thus the ACAC-SVM is proposed for forecasting slope stability. Slope of right-bank spandrel groove at Jinping is forward slope. A majority of the slope surface is bare and comprised of bedrock. the natural slope is comprised of marbleand stability now. The CACA-SVM is used to analysis the stability of the slope of right-bank spandrel groove at Jinping. The results are in good agreement with the actual data, which indicates that the CACA-SVM can be well applied to the analysis of slope stability
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