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• W2783549212 abstract "Non-probabilistic convex model utilizes a convex set to quantify the uncertainty domain of uncertain-but-bounded parameters, which is very effective for structural uncertainty analysis with limited or poor-quality experimental data. To overcome the complexity and diversity of the formulations of current convex models, in this paper, a unified framework for construction of the non-probabilistic convex models is proposed. By introducing the correlation analysis technique, the mathematical expression of a convex model can be conveniently formulated once the correlation matrix of the uncertain parameters is created. More importantly, from the theoretic analysis level, an evaluation criterion for convex modelling methods is proposed, which can be regarded as a test standard for validity verification of subsequent newly proposed convex modelling methods. And from the practical application level, two model assessment indexes are proposed, by which the adaptabilities of different convex models to a specific uncertain problem with given experimental samples can be estimated. Four numerical examples are investigated to demonstrate the effectiveness of the present study." @default.
• W2783549212 created "2018-01-26" @default.
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• W2783549212 creator A5089056035 @default.
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• W2783549212 date "2017-11-29" @default.
• W2783549212 modified "2023-10-16" @default.
• W2783549212 title "Discussions on non-probabilistic convex modelling for uncertain problems" @default.
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• W2783549212 doi "https://doi.org/10.48550/arxiv.1801.05755" @default.
• W2783549212 hasPublicationYear "2017" @default.
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