Machine learning-based methods in structural reliability analysis: A review
Structural Reliability analysis (SRA) is one of the prominent fields in civil and mechanical
engineering. However, an accurate SRA in most cases deals with complex and costly …
engineering. However, an accurate SRA in most cases deals with complex and costly …
A review of machine learning methods applied to structural dynamics and vibroacoustic
Abstract The use of Machine Learning (ML) has rapidly spread across several fields of
applied sciences, having encountered many applications in Structural Dynamics and …
applied sciences, having encountered many applications in Structural Dynamics and …
Assessing small failure probabilities by AK–SS: An active learning method combining Kriging and Subset Simulation
X Huang, J Chen, H Zhu - Structural Safety, 2016 - Elsevier
With complex performance functions and time-demanding computation of structural
responses, the estimation of small failure probabilities is a challenging problem in …
responses, the estimation of small failure probabilities is a challenging problem in …
An adaptive surrogate model to structural reliability analysis using deep neural network
This article introduces a simple and effective adaptive surrogate model to structural reliability
analysis using deep neural network (DNN). In this paradigm, initial design of experiments …
analysis using deep neural network (DNN). In this paradigm, initial design of experiments …
Review and application of artificial neural networks models in reliability analysis of steel structures
This paper presents a survey on the development and use of Artificial Neural Network (ANN)
models in structural reliability analysis. The survey identifies the different types of ANNs, the …
models in structural reliability analysis. The survey identifies the different types of ANNs, the …
An efficient reliability method combining adaptive support vector machine and Monte Carlo simulation
To enhance computational efficiency in reliability analysis, metamodeling has been widely
adopted for reliability assessment. This work develops an efficient reliability method which …
adopted for reliability assessment. This work develops an efficient reliability method which …
Machine learning applied to the design and inspection of reinforced concrete bridges: Resilient methods and emerging applications
W Fan, Y Chen, J Li, Y Sun, J Feng, H Hassanin… - Structures, 2021 - Elsevier
Abstract Machine learning is one of the key pillars of industry 4.0 that has enabled rapid
technological advancement through establishing complex connections among …
technological advancement through establishing complex connections among …
[图书][B] Structural reliability analysis and prediction
RE Melchers, AT Beck - 2018 - books.google.com
Structural Reliability Analysis and Prediction, Third Edition is a textbook which addresses
the important issue of predicting the safety of structures at the design stage and also the …
the important issue of predicting the safety of structures at the design stage and also the …
AKSE: A novel adaptive Kriging method combining sampling region scheme and error-based stopping criterion for structural reliability analysis
The reliability analysis of complex structures usually involves implicit performance function
and expensive-to-evaluate computational models, which pose a great challenge for the …
and expensive-to-evaluate computational models, which pose a great challenge for the …
Rare event estimation using polynomial-chaos kriging
Structural reliability analysis aims at computing the probability of failure of systems whose
performance may be assessed by using complex computational models (eg, expensive-to …
performance may be assessed by using complex computational models (eg, expensive-to …