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IFIP International Conference on Artificial Intelligence Applications and Innovations

AIAI 2021: Artificial Intelligence Applications and Innovations pp 411–422Cite as

Intuitionistic Fuzzy Neural Network for Time Series Forecasting - The Case of Metal Prices

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Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 627))

Abstract

Forecasting time series is an important problem addressed for years. Despite that, it still raises an active interest of researchers. The main issue related to that problem is the inherent uncertainty in data which is hard to be represented in the form of a forecasting model. To solve that issue, a fuzzy model of time series was proposed. Recent developments of that model extend the level of uncertainty involved in data using intuitionistic fuzzy sets. It is, however, worth noting that additional fuzziness exhibits nonlinear behavior. To cope with that issue, we propose a time series model that represents both high uncertainty and non-linearity involved in the data. Specifically, we propose a forecasting model integrating intuitionistic fuzzy sets with neural networks for predicting metal prices. We validate our approach using five financial multivariate time series. The results are compared with those produced by state-of-the-art fuzzy time series models. Thus, we provide solid evidence of high effectiveness of our approach for both one- and five-day-ahead forecasting horizons.

Supported by the scientific research project of the Czech Sciences Foundation Grant No: 19-15498S.

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Author information

Authors and Affiliations

  1. Science and Research Centre, Faculty of Economics and Administration, University of Pardubice, Studentska 84, Pardubice, Czech Republic

    Petr Hajek & Vladimir Olej

  2. Institute of Computer Science, University of Silesia, ul. Bedzinska 39, Sosnowiec, Poland

    Wojciech Froelich

  3. Institute of Business Economics and Management, Faculty of Economics and Administration, University of Pardubice, Studentska 84, Pardubice, Czech Republic

    Josef Novotny

Authors
  1. Petr Hajek
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  2. Vladimir Olej
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  3. Wojciech Froelich
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  4. Josef Novotny
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Corresponding author

Correspondence to Petr Hajek .

Editor information

Editors and Affiliations

  1. University of Piraeus, Piraeus, Greece

    Ilias Maglogiannis

  2. University of Sunderland, Sunderland, UK

    John Macintyre

  3. Democritus University of Thrace, Xanthi, Greece

    Lazaros Iliadis

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Hajek, P., Olej, V., Froelich, W., Novotny, J. (2021). Intuitionistic Fuzzy Neural Network for Time Series Forecasting - The Case of Metal Prices. In: Maglogiannis, I., Macintyre, J., Iliadis, L. (eds) Artificial Intelligence Applications and Innovations. AIAI 2021. IFIP Advances in Information and Communication Technology, vol 627. Springer, Cham. https://doi.org/10.1007/978-3-030-79150-6_33

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  • DOI: https://doi.org/10.1007/978-3-030-79150-6_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-79149-0

  • Online ISBN: 978-3-030-79150-6

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