Gaussian process emulation of spatio-temporal outputs of a 2D inland flood model.

Donnelly, James; Abolfathi, Soroush; Pearson, Jonathan; Chatrabgoun, Omid; Daneshkhah, Alireza

Donnelly, James; Abolfathi, Soroush; Pearson, Jonathan; Chatrabgoun, Omid; Daneshkhah, Alireza.

Afiliação

Donnelly J; Centre for Computational Science and Mathematical Modelling, Coventry University, CV1 5FB, Coventry, United Kingdom; School of Engineering, University of Warwick, CV4 7AL, Coventry, United Kingdom. Electronic address: donnel39@coventry.ac.uk.
Abolfathi S; School of Engineering, University of Warwick, CV4 7AL, Coventry, United Kingdom. Electronic address: Soroush.Abolfathi@Warwick.ac.uk.
Pearson J; School of Engineering, University of Warwick, CV4 7AL, Coventry, United Kingdom.
Chatrabgoun O; School of Computing, Mathematics, and Data Science, Coventry University, CV1 5FB, Coventry, United Kingdom.
Daneshkhah A; Centre for Computational Science and Mathematical Modelling, Coventry University, CV1 5FB, Coventry, United Kingdom; School of Computing, Mathematics, and Data Science, Coventry University, CV1 5FB, Coventry, United Kingdom.

Water Res ; 225: 119100, 2022 Oct 15.

Article em En | MEDLINE | ID: mdl-36155010

Assuntos

Inundações; Redes Neurais de Computação; Simulação por Computador; Hidrodinâmica; Água

Palavras-chave

Dimensionality reduction; Extreme event simulation; Flood prediction; Gaussian process emulator; LISFLOOD-FP; Spatiotemporal outputs

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Inundações Tipo de estudo: Prognostic_studies Idioma: En Revista: Water Res Ano de publicação: 2022 Tipo de documento: Article

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