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Develop 24 dissimilar ANNs by suitable architectures & training algorithms via sensitivity analysis to better statistical presentation: Measure MSEs between targets & ANN for Fe–CuO/Eg–Water nanofluid

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  • Bahrami, Mehrdad
  • Akbari, Mohammad
  • Bagherzadeh, Seyed Amin
  • Karimipour, Arash
  • Afrand, Masoud
  • Goodarzi, Marjan

Abstract

The artificial neural network optimization method is evaluated according to the experimental results of the hybrid non-Newtonian nanofluid of iron and copper oxide in a binary mixture of water and ethylene glycol concerned the mixture dynamic viscosity versus shear rate at different amounts of nanoparticles concentration and temperate. Present work novelty is demonstrated by providing 24 dissimilar ANN methods to introduce the suitable architectures and training algorithms for them. The mean squared errors (MSEs) between the targets and ANN outputs are evaluated to present the best optimization approach among them. Meanwhile the results would be supported by the appropriate sensitivity analysis to have better statistical visual presentation.

Suggested Citation

  • Bahrami, Mehrdad & Akbari, Mohammad & Bagherzadeh, Seyed Amin & Karimipour, Arash & Afrand, Masoud & Goodarzi, Marjan, 2019. "Develop 24 dissimilar ANNs by suitable architectures & training algorithms via sensitivity analysis to better statistical presentation: Measure MSEs between targets & ANN for Fe–CuO/Eg–Water nanofluid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 159-168.
    • Handle: RePEc:eee:phsmap:v:519:y:2019:i:c:p:159-168
    DOI: 10.1016/j.physa.2018.12.031
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    1. M. Goodarzi & M. R. Safaei & A. Karimipour & K. Hooman & M. Dahari & S. N. Kazi & E. Sadeghinezhad, 2014. "Comparison of the Finite Volume and Lattice Boltzmann Methods for Solving Natural Convection Heat Transfer Problems inside Cavities and Enclosures," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-15, February.
    2. Karimipour, Arash & D’Orazio, Annunziata & Goodarzi, Marjan, 2018. "Develop the lattice Boltzmann method to simulate the slip velocity and temperature domain of buoyancy forces of FMWCNT nanoparticles in water through a micro flow imposed to the specified heat flux," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 729-745.
    3. Ahmadi, Gholamreza & Toghraie, Davood & Akbari, Omid Ali, 2017. "Solar parallel feed water heating repowering of a steam power plant: A case study in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 474-485.
    4. Karimipour, Arash & Hemmat Esfe, Mohammad & Safaei, Mohammad Reza & Toghraie Semiromi, Davood & Jafari, Saeed & Kazi, S.N., 2014. "Mixed convection of copper–water nanofluid in a shallow inclined lid driven cavity using the lattice Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 150-168.
    5. Goodarzi, Marjan & D’Orazio, Annunziata & Keshavarzi, Ahmad & Mousavi, Sayedali & Karimipour, Arash, 2018. "Develop the nano scale method of lattice Boltzmann to predict the fluid flow and heat transfer of air in the inclined lid driven cavity with a large heat source inside, Two case studies: Pure natural ," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 210-233.
    6. Safaei, Mohammad Reza & Karimipour, Arash & Abdollahi, Ali & Nguyen, Truong Khang, 2018. "The investigation of thermal radiation and free convection heat transfer mechanisms of nanofluid inside a shallow cavity by lattice Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 515-535.
    7. Khodabandeh, Erfan & Safaei, Mohammad Reza & Akbari, Soheil & Akbari, Omid Ali & Alrashed, Abdullah A.A.A., 2018. "Application of nanofluid to improve the thermal performance of horizontal spiral coil utilized in solar ponds: Geometric study," Renewable Energy, Elsevier, vol. 122(C), pages 1-16.
    8. Jourabian, Mahmoud & Darzi, A. Ali Rabienataj & Toghraie, Davood & Akbari, Omid ali, 2018. "Melting process in porous media around two hot cylinders: Numerical study using the lattice Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 316-335.
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