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System reliability analysis of slopes using least squares support vector machines with particle swarm optimization

机译:最小二乘支持向量机结合粒子群算法的边坡系统可靠性分析。

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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.
机译:本文提出了一种基于最小二乘支持向量机(LSSVM)和粒子群算法的智能响应面法评价土质边坡系统失稳概率。基于计算机实验生成的样本,采用一种新颖的机器学习技术LSSVM来建立响应面以逼近极限状态函数。随后,将建议的响应面与蒙特卡洛模拟结合使用以获得所需的可靠性估计。对于LSSVM性能至关重要的超参数是通过一种称为粒子群优化的群智能算法来选择的。三个实例的实验结果表明,所提出的系统可靠度分析方法对于具有明显系统影响的土质边坡具有广阔的前景。 (C)2016 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Neurocomputing》 |2016年第12期|46-56|共11页
  • 作者单位

    Dalian Univ Technol, Sch Hydraul Engn, Fac Infrastruct Engn, Dalian 116024, Peoples R China|Dalian Univ Technol, State Key Lab Struct Anal Ind Equipment, Dalian 116024, Peoples R China;

    Dalian Univ Technol, Sch Hydraul Engn, Fac Infrastruct Engn, Dalian 116024, Peoples R China;

    Dalian Univ Technol, Sch Hydraul Engn, Fac Infrastruct Engn, Dalian 116024, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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

    机译:边坡稳定性;系统概率分析;LSSVM;粒子群优化;响应面;

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