Hybrid enhanced Monte Carlo simulation coupled with advanced machine learning approach for accurate and efficient structural reliability analysis
type: Item
instance of: scholarly article
title: Hybrid enhanced Monte Carlo simulation coupled with advanced machine learning approach for accurate and efficient structural reliability analysis
author: Changqi Luo
author: Behrooz Keshtegar
author: Shun-Peng Zhu
author: Osman Taylan
author: Xiao-Peng Niu
published in: Computer Methods in Applied Mechanics and Engineering
publication date: 2021-12-13T00:00:00Z
Mathematics Subject Classification ID: 65C05
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 7442788
zbMATH Keywords: enhanced Monte Carlo simulation
zbMATH Keywords: artificial neural network
zbMATH Keywords: structural reliability
zbMATH Keywords: machine learning method
MaRDI profile type: Publication
full work available at URL: j.cma.2021.114218
OpenAlex ID: W3209199687
cites work: Support vector regression based metamodeling for seismic reliability analysis of structures
cites work: Novel probabilistic model for searching most probable point in structural reliability analysis
cites work: A hybrid conjugate finite-step length method for robust and efficient reliability analysis
cites work: Adaptive conjugate single-loop method for efficient reliability-based design and topology optimization
cites work: Three-term conjugate approach for structural reliability analysis
cites work: Some descent three-term conjugate gradient methods and their global convergence
cites work: Novel efficient method for structural reliability analysis using hybrid nonlinear conjugate map-based support vector regression
cites work: Hybrid formulation and solution for transient conjugated conduction-external convection
cites work: A combined projection-outline-based active learning Kriging and adaptive importance sampling method for hybrid reliability analysis with small failure probabilities
cites work: Direct probability integral method for stochastic response analysis of static and dynamic structural systems
cites work: Direct probability integral method for static and dynamic reliability analysis of structures with complicated performance functions
cites work: Chaotic conjugate stability transformation method for structural reliability analysis
cites work: Adaptive kriging-based efficient reliability method for structural systems with multiple failure modes and mixed variables
cites work: Random and multi-super-ellipsoidal variables hybrid reliability analysis based on a novel active learning kriging model
cites work: Efficient reliability analysis with a CDA-based dimension-reduction model and polynomial chaos expansion
cites work: A polynomial expansion approach for response analysis of periodical composite structural-acoustic problems with multi-scale mixed aleatory and epistemic uncertainties
cites work: A radial basis function artificial neural network (RBF ANN) based method for uncertain distributed force reconstruction considering signal noises and material dispersion
cites work: Artificial neural networks in structural dynamics: a new modular radial basis function approach vs. convolutional and feedforward topologies
cites work: Reliability analysis of structures using artificial neural network based genetic algorithms
cites work: A novel projection outline based active learning method and its combination with Kriging metamodel for hybrid reliability analysis with random and interval variables
cites work: A robust iterative algorithm for structural reliability analysis
cites work: Machine learning: Trends, perspectives, and prospects
cites work: A new method for parameter sensitivity estimation in structural reliability analysis
DOI: 10.1016/J.CMA.2021.114218
description: scientific article; zbMATH DE number 7442788