Regional importance effect analysis of the input variables on failure probability

Luyi Li; Zhenzhou Lu

doi:10.1016/j.compstruc.2013.04.026

Regional importance effect analysis of the input variables on failure probability

Luyi Li, Zhenzhou Lu

School of Aeronautics

Northwestern Polytechnical University Xian

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

To analyze the effects of the different regions within input variables on failure probability, a regional importance measure (RIM) is proposed, and its properties are analyzed and verified. The proposed RIM can not only detect the important variables, but also identify regions of the input variable that contribute substantially to the failure probability. To calculate the RIM efficiently, its calculation model is transformed, and the highly efficient adaptive radial-based importance sampling (ARBIS) method is introduced. Numerical and engineering examples have demonstrated the effectiveness of the proposed RIM, and the efficiency and accuracy of the established ARBIS method.

Original language	English
Pages (from-to)	74-85
Number of pages	12
Journal	Computers and Structures
Volume	125
DOIs	https://doi.org/10.1016/j.compstruc.2013.04.026
State	Published - 2013

Keywords

Adaptive radial-based importance sampling
Failure probability
Input variables
Regional importance

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10.1016/j.compstruc.2013.04.026

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abstract = "To analyze the effects of the different regions within input variables on failure probability, a regional importance measure (RIM) is proposed, and its properties are analyzed and verified. The proposed RIM can not only detect the important variables, but also identify regions of the input variable that contribute substantially to the failure probability. To calculate the RIM efficiently, its calculation model is transformed, and the highly efficient adaptive radial-based importance sampling (ARBIS) method is introduced. Numerical and engineering examples have demonstrated the effectiveness of the proposed RIM, and the efficiency and accuracy of the established ARBIS method.",

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AU - Li, Luyi

AU - Lu, Zhenzhou

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AB - To analyze the effects of the different regions within input variables on failure probability, a regional importance measure (RIM) is proposed, and its properties are analyzed and verified. The proposed RIM can not only detect the important variables, but also identify regions of the input variable that contribute substantially to the failure probability. To calculate the RIM efficiently, its calculation model is transformed, and the highly efficient adaptive radial-based importance sampling (ARBIS) method is introduced. Numerical and engineering examples have demonstrated the effectiveness of the proposed RIM, and the efficiency and accuracy of the established ARBIS method.

KW - Adaptive radial-based importance sampling

KW - Failure probability

KW - Input variables

KW - Regional importance

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M3 - 文章

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SN - 0045-7949

VL - 125

SP - 74

EP - 85

JO - Computers and Structures

JF - Computers and Structures

ER -

Regional importance effect analysis of the input variables on failure probability

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Keywords

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