Slope stability analysis based on HS-RVM with mixed kernel
MA Chunhui1，2，YANG Jie1，2，CHENG Lin1，2，LI Ting1，2，WANG Lu1，2
(1. Institute of Water Resources and Hydro-electric Engineering，Xi?an University of Technology，Xi?an，Shaanxi 710048，China；2. State Key Laboratory Base of Eco-hydraulic Engineering in Arid Area，Xi?an University of Technology，Xi?an，Shaanxi 710048，China)
The nonlinear characteristic of the slope stability problem is difficult to be accurately described by the traditional calculation methods，so a slope stability analysis method based on the harmony search(HS) and the relevance vector machine(RVM) is proposed. Considering the characteristics of small sample，nonlinear，high dimension of the slope safety factor prediction，the RVM is employed to quickly calculate the higher accuracy prediction and the posterior probability distribution，and then the confidence interval is established. Since the prediction effect of the RVM depends on the kernel function and its parameters，the mixed kernel function whose generalization and interpolation ability are strong is introduced；the latin hypercube sampling(LHS) is used to initialize the harmony memory；the parameters of mixed kernel function are optimized by the HS. The slope stability analysis method based on the HS-RVM is established with Matlab program，and minimizing mean absolute error(MAE) is used as an optimization target. The application examples show that the HS-RVM gives fully play to the computing power of the HS and the RVM；the HS-RVM is easy to use and has the advantages of high accuracy，high speed；it has good application in the practical engineering calculation.
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2017, Vol. 36 
