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A hybrid fuzzy modeling method for short-term load forecasting

Author

Listed:
  • Mastorocostas, P.A.
  • Theocharis, J.B.
  • Kiartzis, S.J.
  • Bakirtzis, A.G.

Abstract

This paper presents the development of a hybrid fuzzy modeling method for short-term load forecasting. The new approach employs the orthogonal least squares method to create the fuzzy model and a constrained optimization algorithm to perform the parameter learning. The proposed model is tested using data of the Greek power system, while load forecasts with satisfying accuracy are reported.

Suggested Citation

  • Mastorocostas, P.A. & Theocharis, J.B. & Kiartzis, S.J. & Bakirtzis, A.G., 2000. "A hybrid fuzzy modeling method for short-term load forecasting," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 51(3), pages 221-232.
    • Handle: RePEc:eee:matcom:v:51:y:2000:i:3:p:221-232
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    Cited by:

    1. Thomassey, Sebastien & Happiette, Michel & Castelain, Jean-Marie, 2005. "A global forecasting support system adapted to textile distribution," International Journal of Production Economics, Elsevier, vol. 96(1), pages 81-95, April.

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