2019
DOI: 10.1007/s11831-019-09327-x
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Recent Trends in the Modeling and Quantification of Non-probabilistic Uncertainty

Abstract: This paper gives an overview of recent advances in the field of nonprobabilistic uncertainty quantification. Both techniques for the forward propagation and inverse quantification of interval and fuzzy uncertainty are discussed. Also the modeling of spatial uncertainty in an interval and fuzzy context is discussed. An in depth discussion of a recently introduced method for the inverse quantification of spatial interval uncertainty is provided and its performance is illustrated using a case studies taken from l… Show more

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Cited by 114 publications
(79 citation statements)
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“…Besides sampling, there are more sophisticated uncertainty propagation methods such as Polynomial Chaos Expansion (PCE) [87] or Taylor model approximations [57]. Recent trends in UQ are summarized in [58].…”
Section: Non-deterministic Modelsmentioning
confidence: 99%
“…Besides sampling, there are more sophisticated uncertainty propagation methods such as Polynomial Chaos Expansion (PCE) [87] or Taylor model approximations [57]. Recent trends in UQ are summarized in [58].…”
Section: Non-deterministic Modelsmentioning
confidence: 99%
“…Also series‐expansion‐based methods have been presented in the literature (eg, References ). However, these methods are found to be mostly accurate when the intervals are relatively small or when (x) is sufficiently linear . (note: sufficiently implies that the need for linearity of (x) depends on the width of the interval bounds that have to be propagated).…”
Section: Computing With Dependent Intervalsmentioning
confidence: 99%
“…Thực tế, các thông tin này thường chứa đựng các yếu tố ngẫu nhiên, không rõ ràng, không chính xác (thông tin không chắc chắn). Bên cạnh các phương pháp xác suất dựa trên thông tin được mô hình là các đại lượng ngẫu nhiên, phân tích và đánh giá kết cấu theo mô hình mờ cũng thu hút nhiều nghiên cứu [1,2].…”
Section: Giới Thiệuunclassified