Soft Computing

, Volume 22, Issue 9, pp 3023–3032 | Cite as

Modeling of Curie temperature of manganite for magnetic refrigeration application using manual search and hybrid gravitational-based support vector regression

  • Taoreed O. Owolabi
  • Kabiru O. Akande
  • Sunday O. Olatunji
  • Abdullah Alqahtani
  • Nahier Aldhafferid
Methodologies and Application
  • 82 Downloads

Abstract

Magnetic refrigeration (MR) combines many unique features such as low cost, high efficiency and environmental friendliness which make it preferred to the conventional gas compression system of refrigeration. MR employs manganite-based material due to its high magnetocaloric effect as well as tunable Curie temperature (\({T}_{\mathrm{C}}\)). For effective utilization of this technology, \({T}_{\mathrm{C}}\) of manganite refrigerant needs to be tuned to ambient room temperature. In order to relieve experimental stress involved and consequently save valuable time and resources, support vector regression (SVR) computational intelligence technique is proposed using manual search (MS-SVR) and a novel gravitational search algorithm (GSA-SVR) for its hyper-parameter optimization. The developed GSA-SVR model shows better performance than MS-SVR model with performance improvement of 86.03% on the basis of root mean square error (RMSE) and 0.07% on the basis of correlation coefficient (CC) on the training dataset while 11.48% of RMSE improvement and 2.48% of CC improvement were recorded for the testing dataset. The outstanding results presented in this work suggest the potential of the proposed models in promoting room temperature MR through quick estimation of the effect of dopants on \({T}_{\mathrm{C}}\) so as to obtain manganite that works well around the room temperature without loss of precision.

Keywords

Magnetic refrigeration Manganite-based material Curie temperature Gravitational search algorithm Manual search and support vector regression 

Notes

Acknowledgements

The support received from University of Dammam is acknowledged.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with animals performed by any of the authors.

Informed consent

This article does not contain studies with human participants.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Taoreed O. Owolabi
    • 1
    • 2
  • Kabiru O. Akande
    • 3
  • Sunday O. Olatunji
    • 4
  • Abdullah Alqahtani
    • 4
  • Nahier Aldhafferid
    • 4
  1. 1.Physics DepartmentKing Fahd University of Petroleum and MineralsDhahranKingdom of Saudi Arabia
  2. 2.Physics and Electronics DepartmentAdekunle Ajasin UniversityAkungba AkokoNigeria
  3. 3.Institute for Digital Communications, School of EngineeringUniversity of EdinburghEdinburghUK
  4. 4.Computer Information Systems DepartmentUniversity of DammamDammamKingdom of Saudi Arabia

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