Fundamentals of Physics-Informed Neural Networks Applied to Solve the Reynolds Boundary Value Problem

This paper presents a complete derivation and design of a physics-informed neural network (PINN) applicable to solve initial and boundary value problems described by linear ordinary differential equations. The objective with this technical note is not to develop a numerical solution procedure which...

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Vydané v:	Lubricants Ročník 9; číslo 8; s. 82
Hlavný autor:	Almqvist, Andreas
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.08.2021
Predmet:	Bias Boundary value problems Differential equations Finite difference method Finite element method Fluid mechanics Machine Elements Machine learning Maskinelement Meshless methods Neural networks Ordinary differential equations Partial differential equations Physics PINN reynolds equation
ISSN:	2075-4442, 2075-4442
On-line prístup:	Získať plný text
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