Neural Systems for Short-Term Forecasting of Electric Power Load

  • Michał Ba̧k
  • Andrzej Bielecki
Conference paper

DOI: 10.1007/978-3-540-71629-7_16

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4432)
Cite this paper as:
Ba̧k M., Bielecki A. (2007) Neural Systems for Short-Term Forecasting of Electric Power Load. In: Beliczynski B., Dzielinski A., Iwanowski M., Ribeiro B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4432. Springer, Berlin, Heidelberg

Abstract

In this paper a neural system for daily forecasting of electric power load in Poland is presented. Basing on the simplest neural architecture - a multi-layer perceptron - more and more complex system is built step by step. A committee rule-aided hierarchical system consisting of modular ANNs is obtained as a result. The forecasting mean absolute percentage error (MAPE) of the most effective system is about 1.1%.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Michał Ba̧k
    • 1
  • Andrzej Bielecki
    • 1
  1. 1.Institute of Computer Science, Jagiellonian University, Nawojki 11, 30-072 KrakówPoland

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