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Forecasting Energy Demand Using Fuzzy Seasonal Time Series

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Computational Intelligence Systems in Industrial Engineering

Part of the book series: Atlantis Computational Intelligence Systems ((ATLANTISCIS,volume 6))

Abstract

Demand side energy management has become an important issue for energy management. In order to support energy planning and policy decisions forecasting the future demand is very important. Thus, forecasting the future energy demand has gained attention of both academic and professional world. In this chapter, the previous researches on energy demand forecast are classified and fuzzy techniques are introduced. A fuzzy seasonal time series model that forecasts the energy demand is proposed and illustrated with a real world application.

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Authors and Affiliations

  1. Industrial Engineering Department, Istanbul Technical University, Macka Campus, 34367, Istanbul, Turkey

    ˙Irem Uçal Sarı & Ba¸sar Öztay¸si

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  1. ˙Irem Uçal Sarı
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  2. Ba¸sar Öztay¸si
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Correspondence to ˙Irem Uçal Sarı .

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  1. Fac. Management, Dept. Industrial Engineering, Istanbul Technical University, Campus Macka, Istanbul, 34367, Turkey

    Cengiz Kahraman

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Sarı, ˙.U., Öztay¸si, B. (2012). Forecasting Energy Demand Using Fuzzy Seasonal Time Series. In: Kahraman, C. (eds) Computational Intelligence Systems in Industrial Engineering. Atlantis Computational Intelligence Systems, vol 6. Atlantis Press, Paris. https://doi.org/10.2991/978-94-91216-77-0_12

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  • DOI: https://doi.org/10.2991/978-94-91216-77-0_12

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