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International Conference in Artificial Intelligence in Renewable Energetic Systems

ICAIRES 2017: Artificial Intelligence in Renewable Energetic Systems pp 349–354Cite as

Artificial Neural Networks Modeling of an Active Magnetic Refrigeration Cycle

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 35))

Abstract

The aim of this work is to use multi-layered perceptron artificial neural networks and multiple linear regressions models to predict the efficiency of the magnetic refrigeration cycle device operating near room temperature. For this purpose, the experimental data collection was used in order to predict coefficient of performance and temperature span for active magnetic refrigeration device. In addition, the operating parameters of active magnetic refrigerator cycle are used for solid magnetocaloric material under application 1.5 T magnetic fields. The obtained results including temperature span and coefficient of performance are presented and discussed.

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References

  1. Chiba, Y., Smaili, A., Mahmed, C., Balli, M., Sari, O.: Thermal investigations of an experimental active magnetic regenerative refrigerator operating near room temperature. Int. J. Refrig. 37, 36–42 (2014)

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Author information

Authors and Affiliations

  1. Mechanical Engineering Department, Faculty of Technology, University of Medea, Medea, Algeria

    Younes Chiba

  2. LENREZA, Faculté des Mathématiques et Sciences de la Matière, Université de Ouargla, Ouargla, Algeria

    Yacine Marif

  3. LREA, Electrical Engineering Department, Faculty of Technology, University of Medea, Medea, Algeria

    Noureddine Henini & Abdelhalim Tlemcani

Authors
  1. Younes Chiba
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  2. Yacine Marif
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  3. Noureddine Henini
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  4. Abdelhalim Tlemcani
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Corresponding author

Correspondence to Younes Chiba .

Editor information

Editors and Affiliations

  1. EPST-CDER, UDES, Unité de Développement des Equipements Solaires, Bou Ismaïl, Algeria

    Mustapha Hatti

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Chiba, Y., Marif, Y., Henini, N., Tlemcani, A. (2018). Artificial Neural Networks Modeling of an Active Magnetic Refrigeration Cycle. In: Hatti, M. (eds) Artificial Intelligence in Renewable Energetic Systems. ICAIRES 2017. Lecture Notes in Networks and Systems, vol 35. Springer, Cham. https://doi.org/10.1007/978-3-319-73192-6_36

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  • DOI: https://doi.org/10.1007/978-3-319-73192-6_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73191-9

  • Online ISBN: 978-3-319-73192-6

  • eBook Packages: EngineeringEngineering (R0)

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