[HTML][HTML] Adaptive approaches in metamodel-based reliability analysis: A review

R Teixeira, M Nogal, A O'Connor - Structural Safety, 2021 - Elsevier
The present work reviews the implementation of adaptive metamodeling for reliability
analysis with emphasis in four main types of metamodels: response surfaces, polynomial …

Recent advances in reliability analysis of aeroengine rotor system: a review

XQ Li, LK Song, GC Bai - International Journal of Structural Integrity, 2022 - emerald.com
Purpose To provide valuable information for scholars to grasp the current situations,
hotspots and future development trends of reliability analysis area. Design/methodology …

Hybrid and enhanced PSO: Novel first order reliability method-based hybrid intelligent approaches

SP Zhu, B Keshtegar, MEAB Seghier, E Zio… - Computer Methods in …, 2022 - Elsevier
Computing the sensitivity vector in the traditional first order reliability method may provide
inaccurate reliability outcomes for discrete performance functions and inefficient …

Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants

W Chen, H Xu, L Jia, Y Gao - International Journal of Forecasting, 2021 - Elsevier
In recent years, Bitcoin exchange rate prediction has attracted the interest of researchers
and investors. Some studies have used traditional statistical and econometric methods to …

Review and application of artificial neural networks models in reliability analysis of steel structures

AA Chojaczyk, AP Teixeira, LC Neves, JB Cardoso… - Structural safety, 2015 - Elsevier
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 …

Probabilistic analyses of structural dynamic response with modified Kriging-based moving extremum framework

C Lu, CW Fei, YW Feng, YJ Zhao, XW Dong… - Engineering Failure …, 2021 - Elsevier
Mechanical system is usually composed of multiple complex structures, which endure the
combine action of multi-physical fields (eg, flow field, thermal field, structural field, and so …

[HTML][HTML] Quantification of uncertainty modelling in stochastic analysis of FRP composites

S Sriramula, MK Chryssanthopoulos - Composites Part A: Applied Science …, 2009 - Elsevier
The extensive use of FRP composite materials in a wide range of industries, and their
inherent variability, has prompted many researchers to assess their performance from a …

Deep learning for accelerated seismic reliability analysis of transportation networks

MA Nabian, H Meidani - Computer‐Aided Civil and …, 2018 - Wiley Online Library
To optimize mitigation, preparedness, response, and recovery procedures for infrastructure
systems, it is essential to use accurate and efficient means to evaluate system reliability …

An active learning method combining deep neural network and weighted sampling for structural reliability analysis

Z Xiang, J Chen, Y Bao, H Li - Mechanical Systems and Signal Processing, 2020 - Elsevier
Owing to the tremendous computational cost of simulation for large-scale engineering
structures, surrogate model method is widely used as a sample classifier in structural …

Probabilistic stability analyses of slopes using the ANN-based response surface

SE Cho - Computers and Geotechnics, 2009 - Elsevier
Slope stability analysis is a geotechnical engineering problem characterized by many
sources of uncertainty. Some of these sources are connected to the uncertainties of soil …