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Non-Gaussian Quadrature Integral Transform Solution of Parabolic Models with a Finite Degree of Randomness

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Non-Gaussian Quadrature Integral Transform Solution of Parabolic Models with a Finite Degree of Randomness

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Casabán Bartual, MC.; Company Rossi, R.; Jódar Sánchez, LA. (2020). Non-Gaussian Quadrature Integral Transform Solution of Parabolic Models with a Finite Degree of Randomness. Mathematics. 8(7):1-16. https://doi.org/10.3390/math8071112

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/163178

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Metadatos del ítem

Título: Non-Gaussian Quadrature Integral Transform Solution of Parabolic Models with a Finite Degree of Randomness
Autor: Casabán Bartual, Mª Consuelo Company Rossi, Rafael Jódar Sánchez, Lucas Antonio
Entidad UPV: Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada
Fecha difusión:
Resumen:
[EN] In this paper, we propose an integral transform method for the numerical solution of random mean square parabolic models, that makes manageable the computational complexity due to the storage of intermediate information ...[+]
Palabras clave: Random mean square parabolic model , Laplace transform , Numerical inverse Laplace integration , Numerical simulation , Monte Carlo method
Derechos de uso: Reconocimiento (by)
Fuente:
Mathematics. (eissn: 2227-7390 )
DOI: 10.3390/math8071112
Editorial:
MDPI AG
Versión del editor: https://doi.org/10.3390/math8071112
Código del Proyecto:
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-89664-P/ES/PROBLEMAS DINAMICOS CON INCERTIDUMBRE SIMULABLE: MODELIZACION MATEMATICA, ANALISIS, COMPUTACION Y APLICACIONES/
Agradecimientos:
This work has been supported by the Spanish Ministerio de Economia, Industria y Competitividad (MINECO), the Agencia Estatal de Investigacion (AEI) and Fondo Europeo de Desarrollo Regional (FEDER UE) grant MTM2017-89664-P.[+]
Tipo: Artículo

References

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Casaban, M.-C., Cortes, J.-C., & Jodar, L. (2018). Analytic-Numerical Solution of Random Parabolic Models: A Mean Square Fourier Transform Approach. Mathematical Modelling and Analysis, 23(1), 79-100. doi:10.3846/mma.2018.006 [+]
Bharucha-Reid, A. T. (1964). On the theory of random equations. Proceedings of Symposia in Applied Mathematics, 40-69. doi:10.1090/psapm/016/0189071

Ernst, O. G., Sprungk, B., & Tamellini, L. (2018). Convergence of Sparse Collocation for Functions of Countably Many Gaussian Random Variables (with Application to Elliptic PDEs). SIAM Journal on Numerical Analysis, 56(2), 877-905. doi:10.1137/17m1123079

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