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Using Artificial Neural Networks in Fuzzy Time Series Analysis

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Recent Developments and New Directions in Soft Computing

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 317))

Abstract

In recent years, fuzzy time series have been drawn great attention due to their potential for use in time series forecasting. In many studies available in the literature, fuzzy time series have been successfully used to forecast time series contain some uncertainty. Studies on this method still continue to reach better forecasting results. Determination of fuzzy relations between observations is an important phase of fuzzy time series approaches which directly affect the forecasting performance. In order to establish fuzzy relations, different techniques have been utilized in the literature. One of these techniques is artificial neural networks method. In this study, it is shown that how different artificial neural networks models can be used to determine fuzzy relations with real time series applications.

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Author information

Authors and Affiliations

  1. Department of Statistics, Hacettepe University, Beytepe, Ankara, Turkey

    Cagdas Hakan Aladag

Authors
  1. Cagdas Hakan Aladag
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Correspondence to Cagdas Hakan Aladag .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  2. Minister of Communications and Information Technologies of the Republic of Azerbaijan, Baku, Azerbaijan

    Ali M. Abbasov

  3. Iona College, Machine Intelligence Institute, New Rochelle, New York, USA

    Ronald R. Yager

  4. Department of Information Technology and Programming, Azerbaijan Technical University, Baku, Azerbaijan

    Shahnaz N. Shahbazova

  5. Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada

    Marek Z. Reformat

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Aladag, C.H. (2014). Using Artificial Neural Networks in Fuzzy Time Series Analysis. In: Zadeh, L., Abbasov, A., Yager, R., Shahbazova, S., Reformat, M. (eds) Recent Developments and New Directions in Soft Computing. Studies in Fuzziness and Soft Computing, vol 317. Springer, Cham. https://doi.org/10.1007/978-3-319-06323-2_28

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  • DOI: https://doi.org/10.1007/978-3-319-06323-2_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06322-5

  • Online ISBN: 978-3-319-06323-2

  • eBook Packages: EngineeringEngineering (R0)

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