Slope reliability analysis using surrogate models via new support vector machines with swarm intelligence

DOI10.1016/j.apm.2016.01.050zbMath1465.74121OpenAlexW2268859841MaRDI QIDQ2291015

Qing Xu, Fei Kang, Jun-Jie Li

Publication date: 29 January 2020

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2016.01.050

zbMATH Keywords

probabilistic analysisartificial bee colony algorithmsupport vector regressionslope reliabilitySpencer's method

Mathematics Subject Classification ID

Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Monte Carlo methods (65C05) Nonconvex programming, global optimization (90C26) Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and heuristics in mathematical programming (90C59) Soil and rock mechanics (74L10)

Related Items (12)

Active learning relevant vector machine for reliability analysis ⋮ Deep reliability learning with latent adaptation for design optimization under uncertainty ⋮ A fast general extension algorithm of Latin hypercube sampling ⋮ System reliability analysis of slope stability using generalized subset simulation ⋮ Quantitative risk assessment of slope failure in 2-D spatially variable soils by limit equilibrium method ⋮ M5 model tree and Monte Carlo simulation for efficient structural reliability analysis ⋮ A new direct second-order reliability analysis method ⋮ Enriched self-adjusted performance measure approach for reliability-based design optimization of complex engineering problems ⋮ Adaptive cruise control via adaptive dynamic programming with experience replay ⋮ Enhanced channel estimation in OFDM systems with neural network technologies ⋮ Structural damage detection using improved particle swarm optimization ⋮ A new effective operator for the hybrid algorithm for solving global optimisation problems

Uses Software

• LIBSVM
• ABC

Cites Work

• Unnamed Item
• Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions
• Experimentally optimal \(\nu\) in support vector regression for different noise models and parameter settings
• Computer experiments: a review
• Reliability assessment of serviceability performance of braced retaining walls using a neural network approach
• Uniform Design: Theory and Application

This page was built for publication: Slope reliability analysis using surrogate models via new support vector machines with swarm intelligence