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Clustering Techniques Performance Analysis for a Solar Thermal Collector Hybrid Model Implementation

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Hybrid Artificial Intelligent Systems (HAIS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12344))

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Abstract

This work addresses the performance comparison of clustering techniques in order to achieve robust hybrid models. With this goal, three different clustering techniques have been tested. The experimental environment designed for this purpose is based on a real case study, a thermal solar generation system installed in a bio-climate house located in Sotavento Experimental Wind Farm, in Xermade (Lugo) in Galicia (Spain). In this way, clustering methods have been applied over the real dataset extracted from the thermal solar generation installation.

For comparing the quality of each clustering technique, two approaches have been used. The first one is oriented to a set of three unsupervised learning metrics (Silhouette, Calinski-Harabasz, and Davies-Bouldin), while the second one is based on error measurements associated with a regression method such as Multi-Layer Perceptron.

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Acknowledgements

This work is partially supported by Junta de Castilla y Leon - Consejería de Educacion. Project: LE078G18. UXXI2018/000149. U-220.

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Authors and Affiliations

  1. Department of Electrical and Systems Engineering, University of León, Escuela de Ingenierías, Campus de Vegazana, 24071, León, Spain

    María Teresa García-Ordás, Héctor Alaiz-Moretón, José Alberto Benítez Andrades & Carmen Benavides Cuellar

  2. CTC, Department of Industrial Engineering, CITIC, University of A Coruña, Avda. 19 de febrero s/n, 15405, Ferrol, A Coruña, Spain

    José-Luis Casteleiro-Roca, Esteban Jove, Héctor Quintián & José Luis Calvo-Rolle

Authors
  1. María Teresa García-Ordás
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  2. Héctor Alaiz-Moretón
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  3. José-Luis Casteleiro-Roca
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  4. Esteban Jove
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  5. José Alberto Benítez Andrades
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  6. Carmen Benavides Cuellar
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  7. Héctor Quintián
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  8. José Luis Calvo-Rolle
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Corresponding author

Correspondence to José-Luis Casteleiro-Roca .

Editor information

Editors and Affiliations

  1. University of Oviedo, Oviedo, Spain

    Enrique Antonio de la Cal

  2. University of Oviedo, Oviedo, Spain

    José Ramón Villar Flecha

  3. University of A Coruña, Ferrol, Spain

    Héctor Quintián

  4. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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García-Ordás, M.T. et al. (2020). Clustering Techniques Performance Analysis for a Solar Thermal Collector Hybrid Model Implementation. In: de la Cal, E.A., Villar Flecha, J.R., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2020. Lecture Notes in Computer Science(), vol 12344. Springer, Cham. https://doi.org/10.1007/978-3-030-61705-9_27

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  • DOI: https://doi.org/10.1007/978-3-030-61705-9_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61704-2

  • Online ISBN: 978-3-030-61705-9

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