Numerical Investigation of a Class of Nonlinear Time-Dependent Delay PDEs Based on Gaussian Process Regression

Numerical Investigation of a Class of Nonlinear Time-Dependent Delay PDEs Based on Gaussian Process Regression

Probabilistic machine learning and data-driven methods gradually show their high efficiency in solving the forward and inverse problems of partial differential equations (PDEs). This paper will focus on investigating the forward problem of solving time-dependent nonlinear delay PDEs with multi-delay...

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Bibliographic Details
Main Authors: Wei Gu, Wenbo Zhang, Yaling Han
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Fractal and Fractional
Subjects:
probabilistic machine learning
multi-prior numerical Gaussian processes
nonlinear time-dependent delay partial differential equations
fractional partial differential equations
mixed boundary conditions
Runge–Kutta methods
Online Access:https://www.mdpi.com/2504-3110/6/10/606

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https://www.mdpi.com/2504-3110/6/10/606

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