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FUTURA: Hybrid System for Electric Load Forecasting by Using Case-Based Reasoning and Expert System

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Topics in Artificial Intelligence (CCIA 2002)

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Abstract

The results of combining a numeric extrapolation of data with the methodology of case-based reasoning and expert systems in order to improve the electric load forecasting are presented in this contribution. Registers of power consumption are stored as cases that are retrieved and adapted by an expert system to improve a numeric forecasting given by numeric algorithms. FUTURA software has been developed as a result of this work. It combines the proposed techniques in a modular way while it provides a graphic user interface and access capabilities to existing data bases.

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Author information

Authors and Affiliations

  1. Institut d’Informàtica i Aplicacions, Universitat de Girona, Campus Montilivi, Edifici P.4., Girona, Spain

    Raúl Vilcahuamán, Joaquim Meléndez & Josep Lluis de la Rosa

  2. Facultad de Ingenierίa de Sistemas, Universidad Nacional del Centro del Perú, Calle Real 160, Huancayo, Perú

    Raúl Vilcahuamán

Authors
  1. Raúl Vilcahuamán
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  2. Joaquim Meléndez
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  3. Josep Lluis de la Rosa
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Editor information

Editors and Affiliations

  1. Departament d’Enginyeria i Ciència dels Computadors, Universitat Jaume 1, Campus de Riu Sec, 12071, Castellón, Spain

    M. Teresa Escrig  & Francisco Toledo  & 

  2. Computer Science Department, Universitat Ramon Llull, Passeig Bonanova, 8, 08022, Barcelona, Catalunya, Spain

    Elisabet Golobardes

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© 2002 Springer-Verlag Berlin Heidelberg

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Vilcahuamán, R., Meléndez, J., de la Rosa, J.L. (2002). FUTURA: Hybrid System for Electric Load Forecasting by Using Case-Based Reasoning and Expert System. In: Escrig, M.T., Toledo, F., Golobardes, E. (eds) Topics in Artificial Intelligence. CCIA 2002. Lecture Notes in Computer Science(), vol 2504. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36079-4_11

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  • DOI: https://doi.org/10.1007/3-540-36079-4_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00011-2

  • Online ISBN: 978-3-540-36079-7

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