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Data Mining Methods for Long-Term Forecasting of Market Demand for Industrial Goods

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Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems Architecture and Technology – ISAT 2015 – Part IV

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 432))

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Abstract

This paper proposes a new method for long-term forecasting of level and structure of market demand for industrial goods. The method employs k-means clustering and fuzzy decision trees to obtain the required forecast. The k-means clustering serves to separate groups of items with similar level and structure (pattern) of steel products consumption. Whereas, fuzzy decision tree is used to determine the dependencies between consumption patterns and predictors. The proposed method is verified using the extensive statistical material on the level and structure of steel products consumption in selected countries over the years 1960–2010.

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Authors and Affiliations

  1. AGH University of Science and Technology, Kraków, Poland

    Bartłomiej Gaweł, Bogdan Rębiasz & Iwona Skalna

Authors
  1. Bartłomiej Gaweł
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  2. Bogdan Rębiasz
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  3. Iwona Skalna
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Corresponding author

Correspondence to Bartłomiej Gaweł .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Manageme, Wrocław University of Technology, Wrocła, Wrocław, Poland

    Zofia Wilimowska

  2. Faculty of Computer Science and Manageme, Wrocław University of Technology, Wrocła, Wroclaw, Poland

    Leszek Borzemski

  3. Faculty of Computer Science and Manageme, Wrocław University of Technology, Wrocła, Wrocław, Poland

    Adam Grzech

  4. Faculty of Computer Science and Manageme, Wrocław University of Technology, Wrocła, Wrocław, Poland

    Jerzy Świątek

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Gaweł, B., Rębiasz, B., Skalna, I. (2016). Data Mining Methods for Long-Term Forecasting of Market Demand for Industrial Goods. In: Wilimowska, Z., Borzemski, L., Grzech, A., Świątek, J. (eds) Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems Architecture and Technology – ISAT 2015 – Part IV. Advances in Intelligent Systems and Computing, vol 432. Springer, Cham. https://doi.org/10.1007/978-3-319-28567-2_1

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  • DOI: https://doi.org/10.1007/978-3-319-28567-2_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28565-8

  • Online ISBN: 978-3-319-28567-2

  • eBook Packages: EngineeringEngineering (R0)

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