Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

V Nemani, L Biggio, X Huan, Z Hu, O Fink… - … Systems and Signal …, 2023 - Elsevier
On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an
essential layer of safety assurance that could lead to more principled decision making by …

[HTML][HTML] Mountaineering team-based optimization: A novel human-based metaheuristic algorithm

I Faridmehr, ML Nehdi, IF Davoudkhani, A Poolad - Mathematics, 2023 - mdpi.com
This paper proposes a novel optimization method for solving real-world optimization
problems. It is inspired by a cooperative human phenomenon named the mountaineering …

A Review of Recent Advances in Surrogate Models for Uncertainty Quantification of High-Dimensional Engineering Applications

Z Azarhoosh, MI Ghazaan - Computer Methods in Applied Mechanics and …, 2025 - Elsevier
In fields where predictions may have vital consequences, uncertainty quantification (UQ)
plays a crucial role, as it enables more accurate forecasts and mitigates the potential risks …

Efficient adaptive Kriging-based reliability analysis combining new learning function and error-based stop** criterion

J Yi, Q Zhou, Y Cheng, J Liu - Structural and Multidisciplinary Optimization, 2020 - Springer
The Kriging-based reliability analysis is extensively adopted in engineering structural
reliability analysis for its capacity to achieve accurate failure probability estimation with high …

A new sampling approach for system reliability-based design optimization under multiple simulation models

S Yang, M Lee, I Lee - Reliability Engineering & System Safety, 2023 - Elsevier
In this paper, a new system reliability-based design optimization (SRBDO) method is
proposed for problems where performance function values are obtained from different …

A novel Bayesian optimization for flow condensation enhancement using nanorefrigerant: a combined analytical and experimental study

B Rezaeianjouybari, M Sheikholeslami… - Chemical Engineering …, 2020 - Elsevier
According to the recent researches, adding nanomaterial within the pure refrigerant can
substantially enhance the heat transfer rate in phase change (boiling/condensing) flows …

Portfolio allocation strategy for active learning Kriging-based structural reliability analysis

L Hong, B Shang, S Li, H Li, J Cheng - Computer Methods in Applied …, 2023 - Elsevier
Recently, numerous studies have focused on structural reliability analysis, with the Kriging-
based active learning method being particularly popular. A variety of Kriging-based learning …