AUTOMATIC SELECTION OF BASIS-ADAPTIVE SPARSE POLYNOMIAL CHAOS EXPANSIONS FOR ENGINEERING APPLICATIONS | Zendy

Nora Lüthen | Zendy; Stefano Marelli | Zendy; Bruno Sudret | Zendy

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AUTOMATIC SELECTION OF BASIS-ADAPTIVE SPARSE POLYNOMIAL CHAOS EXPANSIONS FOR ENGINEERING APPLICATIONS

Author(s) -

Nora Lüthen,

Stefano Marelli,

Bruno Sudret

Publication year - 2021

Publication title -

international journal for uncertainty quantification

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.664

H-Index - 21

eISSN - 2152-5099

pISSN - 2152-5080

DOI - 10.1615/int.j.uncertaintyquantification.2021036153

Subject(s) - benchmark (surveying) , solver , computer science , polynomial chaos , basis (linear algebra) , set (abstract data type) , dimension (graph theory) , uncertainty quantification , polynomial basis , selection (genetic algorithm) , surrogate model , polynomial , mathematical optimization , basis function , lasso (programming language) , algorithm , machine learning , mathematics , monte carlo method , mathematical analysis , statistics , geometry , geodesy , world wide web , pure mathematics , programming language , geography

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