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Neural Computing and Applications

, Volume 31, Supplement 2, pp 1291–1298 | Cite as

Modeling of magnetic cooling power of manganite-based materials using computational intelligence approach

  • Taoreed O. Owolabi
  • Luqman E. OlooreEmail author
  • Kabiru O. Akande
  • Sunday O. Olatunji
Original Article

Abstract

Magnetic refrigeration (MR) technology has been identified as a potential replacement for the gas compression system of refrigeration due to its environmental friendliness and high level of efficiency. This technology utilizes manganite-based materials as magnetic refrigerants due to the dependence of magnetic properties as well as relative cooling power (RCP) of this class of materials on the concentration and nature of the dopants. Quantifying the effect of dopants on RCP of manganite-based materials requires a long experimental procedures and techniques that are costly and time-consuming. In order to circumvent these challenges, we propose a model, based on support vector regression (SVR), which quickly estimates the RCP of doped manganite-based materials with high level of accuracy using crystal lattice constants as descriptors. The accuracy and ease with which the proposed SVR-based model estimates RCP of doped manganite-based materials is very promising and effective in designing MR system of desired RCP.

Keywords

Relative cooling power Support vector regression Manganite-based materials Lattice constants Magnetic refrigeration 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interest as this manuscript represents original research work.

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Copyright information

© The Natural Computing Applications Forum 2017

Authors and Affiliations

  • Taoreed O. Owolabi
    • 1
    • 2
  • Luqman E. Oloore
    • 1
    • 3
    Email author
  • Kabiru O. Akande
    • 4
  • Sunday O. Olatunji
    • 5
  1. 1.Physics DepartmentKing Fahd University of Petroleum and MineralsDhahranKingdom of Saudi Arabia
  2. 2.Physics and Electronics DepartmentAdekunle Ajasin UniversityAkungba AkokoNigeria
  3. 3.Physics and Engineering Physics DepartmentObafemi Awolowo UniversityIle-IfeNigeria
  4. 4.Electrical Engineering DepartmentUniversity of EdinburghEdinburghUK
  5. 5.Computer Science DepartmentUniversity of DammamDammamKingdom of Saudi Arabia

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