A Data Driven Black Box Approach for the Inverse Quantification of Set-Theoretical Uncertainty

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Journal
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering
Published
2024-09-26
DOI
https://doi.org/10.1115/1.4066619
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
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article

A Data Driven Black Box Approach for the Inverse Quantification of Set-Theoretical Uncertainty

Matthias G.R. Faes, Lars Bogaerts, David Moens
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering
Probabilistic and Robust Engineering Design
article

A Data Driven Black Box Approach for the Inverse Quantification of Set-Theoretical Uncertainty

Matthias G.R. Faes, Lars Bogaerts, David Moens
article en

Abstract

No abstract available for this paper.
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical EngineeringVol. 11(3)
TU Dortmund University (DE), Flanders Make (Belgium) (BE), KU Leuven (BE)
Openalex Percentile: Top 84%
Probabilistic and Robust Engineering Design
DOIOpen Access PDFOpenAlex
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