Optimal fuzzy inference for short-term load forecasting

Hiroyuki Mori, Hidenori Kobayashi

Research output: Contribution to journalArticle

159 Citations (Scopus)


This paper proposes an optimal fuzzy inference method for short-term load forecasting. The proposed method constructs an optimal structure of the simplified fuzzy inference that minimizes model errors and the number of the membership functions to grasp nonlinear behavior of power system short-term loads. The model is identified by simulated annealing and the steepest descent method. The proposed method is demonstrated in examples.

Original languageEnglish
Pages (from-to)390-396
Number of pages7
JournalIEEE Transactions on Power Systems
Issue number1
Publication statusPublished - 1 Dec 1996



  • Fuzzy inference
  • Nonlinear approximation
  • Short-term load forecasting
  • Simulated annealing
  • Supervised learning

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