Optimal control of thermoregulation in the human dermal regions investigated through the stochastic integrated techniques

Ahmad, Iftikhar; Hussain, Syed Ibrar; Ilyas, Hira; Raja, Muhammad Asif Zahoor; Afzal, Sana; Javed, Mariam

doi:10.1016/j.csite.2024.104381

Case Studies in Thermal Engineering

2024

DOI: 10.1016/j.csite.2024.104381

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Optimal control of thermoregulation in the human dermal regions investigated through the stochastic integrated techniques

Iftikhar Ahmad,

Syed Ibrar Hussain,

Hira Ilyas

et al.

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2024

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Cited by 4 publications

References 52 publications

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Radial basis kernel harmony in neural networks for the analysis of MHD Williamson nanofluid flow with thermal radiation and chemical reaction: An evolutionary approach

Butt,

Raja,

Ahmad

et al. 2024

Alexandria Engineering Journal

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Radial basis kernel harmony in neural networks for the analysis of MHD Williamson nanofluid flow with thermal radiation and chemical reaction: An evolutionary approach

Butt,

Raja,

Ahmad

et al. 2024

Alexandria Engineering Journal

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Stochastic neuro-swarming intelligence paradigm for the analysis of magneto-hydrodynamic Prandtl–Eyring fluid flow with diffusive magnetic layers effect over an elongated surface

Butt,

Ahmad,

Shoaib

et al. 2024

Chinese Journal of Chemical Engineering

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Design of stochastic computational Levenberg Marquardt backpropagation-based technique to investigate temperature distribution of longitudinal moving porous fin

Ahmad,

Raja,

Hussain

et al. 2024

Sci Rep

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The improvement of thermal exchange is of utmost interest in a wide range of engineering areas. The current study focuses on thermal evaluation involving natural radiation and convection in a fractionally arranged moving longitudinal fin model placed under a magnetic field. We implement the Levenberg Marquardt backpropagation (LMB) algorithm for investigating an innovative use of stochastic numerical computation for analyzing the efficiency of the temperature distribution in a porous moving longitudinal fin. The datasets for LMB have been created using a shooting approach for dynamic systems with varying ranges of different parameters. The validation, testing, and training processes are used to simulate networks using the LMB approach for diverse scenarios of moving porous fin models. The reliability of results is assessed based on the regression measures, absolute error, error histograms, mean square error, and other metrics for fuller numerical modeling of the suggested LMB to investigate the thermal efficiency and effectiveness of porous moving fin.

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Optimal control of thermoregulation in the human dermal regions investigated through the stochastic integrated techniques

Cited by 4 publications

References 52 publications

Radial basis kernel harmony in neural networks for the analysis of MHD Williamson nanofluid flow with thermal radiation and chemical reaction: An evolutionary approach

Radial basis kernel harmony in neural networks for the analysis of MHD Williamson nanofluid flow with thermal radiation and chemical reaction: An evolutionary approach

Stochastic neuro-swarming intelligence paradigm for the analysis of magneto-hydrodynamic Prandtl–Eyring fluid flow with diffusive magnetic layers effect over an elongated surface

Design of stochastic computational Levenberg Marquardt backpropagation-based technique to investigate temperature distribution of longitudinal moving porous fin

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