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论文类型：期刊论文

发表时间：2016-10-12

发表刊物：NEUROCOMPUTING

收录刊物：SCIE、EI、Scopus

卷号：209

页面范围：46-56

ISSN号：0925-2312

关键字：Slope stability; System probabilistic analysis; LSSVM; Particle swarm optimization; Response surface

摘要：This paper presents an intelligent response surface method for evaluating system failure probability of soil slopes based on least squares support vector machines (LSSVM) and particle swarm optimization. A novel machine learning technique LSSVM is adopted to establish the response surface to approximate the limit state function based on the samples generated by computer experiments. Subsequently, the proposed response surface is utilized in conjunction with Monte Carlo simulation to obtain the desired reliability estimation. The hyper-parameters which are crucial to the performance of LSSVM are selected by a swarm intelligence algorithm called particle swarm optimization. Experimental results on three examples show that the proposed system reliability analysis method is promising for soil slopes with obvious system effects. (C) 2016 Elsevier B.V. All rights reserved.