A Levenberg–Marquardt Backpropagation Neural Network for the Numerical Treatment of Squeezing Flow With Heat Transfer Model

A Levenberg–Marquardt Backpropagation Neural Network for the Numerical Treatment of Squeezing Flow With Heat Transfer Model

In this paper, the computational strength in terms of soft computing neural networks backpropagated with the efficacy of Levenberg-Marquard training (NN-BLMT) is presented to study the squeezing flow with the heat transfer model (SF-HTM). The governing system of PDEs is reduced to an equivalent syst...

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Bibliographic Details
Main Authors: Maryam Mabrook Almalki, Eman Salem Alaidarous, Dalal Adnan Maturi, Muhammad Asif Zahoor Raja, Muhammad Shoaib
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Squeezing flow
heat transfer
soft computing infrastructure
neural networks backpropagated
Levenberg-Marquard training
Online Access:https://ieeexplore.ieee.org/document/9296207/

Internet

https://ieeexplore.ieee.org/document/9296207/

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