Design of a unified physics-informed neural network using interior point algorithm to study the bioconvection nanofluid flow via stretching surface-Reference-Cited by-同舟云学术

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Design of a unified physics-informed neural network using interior point algorithm to study the bioconvection nanofluid flow via stretching surface

Published:2024-07 Issue: Volume:133 Page:108647
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Chandra Priyanka^ORCID,Das Raja^ORCID

Publisher

Elsevier BV

Reference61 articles.

1. Numerical simulation of the nanofluid flow consists of gyrotactic microorganism and subject to activation energy across an inclined stretching cylinder;Othman;Sci. Rep.,2023

2. Solutions of fractional order differential equations modeling temperature distribution in convective straight fins design;Ahmad;Adv. Differ. Equ.,2021

3. Analysis of a mathematical model for drilling system with reverse air circulation by using the ANN-BHCS technique;Ahmad;IEEE Access,2021

4. Mixed convective flow of hybrid nanofluid over a heated stretching disk with zero-mass flux using the modified Buongiorno model;Ali;Alex. Eng. J.,2023

5. Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation;Arzani;J. Comput. Phys.,2023

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