A novel design of Gaussian WaveNets for rotational hybrid nanofluidic flow over a stretching sheet involving thermal radiation

The aim of this study is to analysis the mass and heat transfer in radiative three dimensional flow of hybrid nanofluid over the stretchable sheet by exploiting the strength of integrated computational intelligent algorithm by utilization of Gaussian wavelet neural networks (GWNNs) trained with the...

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Published in:International communications in heat and mass transfer Vol. 123; p. 105196
Main Authors: Ilyas, Hira, Ahmad, Iftikhar, Raja, Muhammad Asif Zahoor, Shoaib, Muhammad
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.04.2021
Subjects:
Gaussian wavelets
Genetic algorithms
Hybrid nanofluid
Neural networks
Sequential quadratic programming
Stochastic numerical computing
Stretching sheet
Stochastic numerical computing
Sequential quadratic programming
Neural networks
Gaussian wavelets
Stretching sheet
Genetic algorithms
Hybrid nanofluid
ISSN:0735-1933, 1879-0178
Online Access:Get full text
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Abstract The aim of this study is to analysis the mass and heat transfer in radiative three dimensional flow of hybrid nanofluid over the stretchable sheet by exploiting the strength of integrated computational intelligent algorithm by utilization of Gaussian wavelet neural networks (GWNNs) trained with the genetic algorithms (GAs) based global search supported with sequential quadratic programming (SQP) based local refinements i.e., GWNN-GA-SQP. The mean squared error based cost function is developed for the fluidic problem by applying Gaussian WaveNet GWNNs optimize with GAs and SQP. The numerical outcomes of the fluidic model are obtained by the proposed GWNN-GA-SQP solver to examine the thermal and velocities profile effect for three physical quantities based on magnetic parameter, nanomaterial concentration and transformated angular velocity. Moreover, a exhaustive analysis of the numerical solutions of GWNN-GA-SQP solver with reference Adams method endorse the stability, accuracy and consistency on multiple autonomous runs through different statistical performance operators and complexity analysis. [Display omitted]
AbstractList The aim of this study is to analysis the mass and heat transfer in radiative three dimensional flow of hybrid nanofluid over the stretchable sheet by exploiting the strength of integrated computational intelligent algorithm by utilization of Gaussian wavelet neural networks (GWNNs) trained with the genetic algorithms (GAs) based global search supported with sequential quadratic programming (SQP) based local refinements i.e., GWNN-GA-SQP. The mean squared error based cost function is developed for the fluidic problem by applying Gaussian WaveNet GWNNs optimize with GAs and SQP. The numerical outcomes of the fluidic model are obtained by the proposed GWNN-GA-SQP solver to examine the thermal and velocities profile effect for three physical quantities based on magnetic parameter, nanomaterial concentration and transformated angular velocity. Moreover, a exhaustive analysis of the numerical solutions of GWNN-GA-SQP solver with reference Adams method endorse the stability, accuracy and consistency on multiple autonomous runs through different statistical performance operators and complexity analysis. [Display omitted]
ArticleNumber 105196
Author Ilyas, Hira
Raja, Muhammad Asif Zahoor
Shoaib, Muhammad
Ahmad, Iftikhar
Author_xml – sequence: 1
  givenname: Hira
  surname: Ilyas
  fullname: Ilyas, Hira
  email: 17016109-003@uog.edu.pk
  organization: Department of Mathematics, University of Gujrat, Gujrat 50700, Pakistan
– sequence: 2
  givenname: Iftikhar
  surname: Ahmad
  fullname: Ahmad, Iftikhar
  email: dr.iftikhar@uog.edu.pk
  organization: Department of Mathematics, University of Gujrat, Gujrat 50700, Pakistan
– sequence: 3
  givenname: Muhammad Asif Zahoor
  surname: Raja
  fullname: Raja, Muhammad Asif Zahoor
  email: rajamaz@yuntech.edu.tw
  organization: Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, ROC
– sequence: 4
  givenname: Muhammad
  surname: Shoaib
  fullname: Shoaib, Muhammad
  email: dr.shoaib@cuiatk.edu.pk
  organization: Department of Mathematics, COMSATS University Islamabad, Attock Campus, Attock 43600, Pakistan
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Keywords Stochastic numerical computing
Sequential quadratic programming
Neural networks
Gaussian wavelets
Stretching sheet
Genetic algorithms
Hybrid nanofluid
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SSID ssj0001818
Score 2.516475
Snippet The aim of this study is to analysis the mass and heat transfer in radiative three dimensional flow of hybrid nanofluid over the stretchable sheet by...
SourceID crossref
elsevier
SourceType Enrichment Source
Index Database
Publisher
StartPage 105196
SubjectTerms Gaussian wavelets
Genetic algorithms
Hybrid nanofluid
Neural networks
Sequential quadratic programming
Stochastic numerical computing
Stretching sheet
Title A novel design of Gaussian WaveNets for rotational hybrid nanofluidic flow over a stretching sheet involving thermal radiation
URI https://dx.doi.org/10.1016/j.icheatmasstransfer.2021.105196
Volume 123
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