A novel nonlinear regression model of SVR as a substitute for ANN to predict conductivity of MWCNT-CuO/water hybrid nanofluid based on empirical data Article

Karimipour, Arash, Bagherzadeh, Seyed Amin, Taghipour, Abdolmajid et al. (2019). A novel nonlinear regression model of SVR as a substitute for ANN to predict conductivity of MWCNT-CuO/water hybrid nanofluid based on empirical data . PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 521 89-97. 10.1016/j.physa.2019.01.055

ESI Most Cited Paper International Collaboration

cited authors

  • Karimipour, Arash; Bagherzadeh, Seyed Amin; Taghipour, Abdolmajid; Abdollahi, Ali; Safaei, Mohammad Reza

authors

publication date

  • May 1, 2019

published in

keywords

  • ARTIFICIAL NEURAL-NETWORK
  • COPPER-WATER NANOFLUID
  • HEAT-TRANSFER
  • Hybrid nanofluid
  • LATTICE BOLTZMANN
  • LID-DRIVEN CAVITY
  • MAGNETO-NATURAL CONVECTION
  • Optimization
  • Physical Sciences
  • Physics
  • Physics, Multidisciplinary
  • Regression approach
  • SLIP VELOCITY
  • SOLID VOLUME FRACTION
  • Science & Technology
  • THERMAL-CONDUCTIVITY
  • Thermal conductivity
  • WALL CARBON NANOTUBES

Digital Object Identifier (DOI)

publisher

  • ELSEVIER

start page

  • 89

end page

  • 97

volume

  • 521