Abstract
For energy planning, forecasting the energy demand for a specific time interval and supply of a specific source is very crucial. In the energy sector, forecasting may be long term, midterm or short term. While traditional forecasting techniques provide results for crisp data, for data with imprecision or vagueness fuzzy based approaches can be used. In this chapter, fuzzy forecasting methods such as, fuzzy time series (FTS), fuzzy regression, adaptive network-based fuzzy inference system (ANFIS) and fuzzy inference systems (FIS) as explained. Later, an extended literature review of fuzzy forecasting in energy planning is provided. Finally, a numerical application is given to give a better understanding of fuzzy forecasting approaches.
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As a specialist in Information Technologies Department, Eda Bolturk thanks İstanbul Takas ve Saklama Bankası A.S. for getting support for this study.
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Oztaysi, B., Çevik Onar, S., Bolturk, E., Kahraman, C. (2018). Fuzzy Forecasting Methods for Energy Planning. In: Kahraman, C., Kayakutlu, G. (eds) Energy Management—Collective and Computational Intelligence with Theory and Applications. Studies in Systems, Decision and Control, vol 149. Springer, Cham. https://doi.org/10.1007/978-3-319-75690-5_4
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