Analysing Concentrating Photovoltaics Technology Through the Use of Emerging Pattern Mining

  1. García-Vico, A.M. 1
  2. J. Montes 1
  3. J. Aguilera 1
  4. Carmona, C.J. 2
  5. Jesus, M.J. del 1
  1. 1 Universidad de Jaén
    info

    Universidad de Jaén

    Jaén, España

    ROR https://ror.org/0122p5f64

  2. 2 Universidad de Burgos
    info

    Universidad de Burgos

    Burgos, España

    ROR https://ror.org/049da5t36

Libro:
International Joint Conference SOCO’16-CISIS’16-ICEUTE’16: San Sebastián, Spain, October 19th-21st, 2016 Proceedings
  1. Manuel Graña (coord.)
  2. José Manuel López-Guede (coord.)
  3. Oier Etxaniz (coord.)
  4. Álvaro Herrero (coord.)
  5. Héctor Quintián (coord.)
  6. Emilio Corchado (coord.)

Editorial: Springer Suiza

ISBN: 978-3-319-47364-2,  3-319-47364-6,  978-3-319-47363-5,  3-319-47363-8

Año de publicación: 2017

Páginas: 334-344

Congreso: International Conference on Computational Intelligence in Security for Information Systems (9. 2016. San Sebastián)

Tipo: Aportación congreso

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Resumen

The search of emerging patterns pursues the description of a problem through the obtaining of trends in the time, or characterisation of differences between classes or group of variables. This contribution presents an application to a real-world problem related to the photovoltaic technology through the algorithm EvAEP. Specifically, the algorithm is an evolutionary fuzzy system for emerging pattern mining applied to a problem of concentrating photovoltaic technology which is focused on the generation of electricity reducing the associated costs. Emerging pattern shave discovered relevant information for the experts when the maximum power is reached for the cells of concentrating photovoltaic.

Fuente de los datos: Dialnet