Slope stability analysis based on quantum-behaved particle swarm optimization and least squares support vector machine
作者: Bo LiDuanyou LiZhijun ZhangShengmei YangFan Wang
作者单位: 1Engineering Safety and Disaster Prevention Department, Changjiang River Scientific Research Institute, Wuhan, Hubei 430010, China
2Construction and Design Department, Changjiang Institute of Survey, Planning, Design and Research, Wuhan, Hubei 430010, China
刊名: Applied Mathematical Modelling, 2015, Vol.39 (17), pp.5253-5264
来源数据库: Elsevier Journal
DOI: 10.1016/j.apm.2015.03.032
关键词: Slope stabilityQuantum-behaved particle swarm optimizationLeast squares support machine
英文摘要: Abstract(#br)Given the complexity and uncertainty of the influencing factors of slope stability, its accurate evaluation is difficult to accomplish using conventional approaches. This paper presents the use of a least square support vector machine (LSSVM) algorithm based on quantum-behaved particle swarm optimization (QPSO) to establish the nonlinear relationship of slope stability. In the proposed QPSO-LSSVM algorithm, QPSO is employed to optimize the important parameters of LSSVM. To identify the local and global optimum, three popular benchmark functions are utilized to test the abilities of the proposed QPSO, the nonlinearly decreasing weight PSO, and the linearly decreasing weight PSO algorithms. The proposed QPSO exhibited superior performance over the other aforementioned...
全文获取路径: Elsevier  (合作)
影响因子:1.706 (2012)

  • optimization 最佳化
  • swarm 
  • machine 机器
  • support 支柱
  • stability 稳定性
  • particle 颗粒
  • least 最少的
  • quantum 量子
  • vector 矢量
  • based 基于