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A Linguistic Approach to a Human-Consistent Summarization of Time Series Using a SOM Learned with a LVQ-Type Algorithm

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Artificial Neural Networks – ICANN 2006 (ICANN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4132))

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Abstract

The purpose of this paper is to propose a new, human consistent way to capture the very essence of a dynamic behavior of some sequences of numerical data. Instead of using traditional, notably statistical type analyses, we propose the use of fuzzy logic based linguistic summaries of data(bases) in the sense of Yager, later developed by Kacprzyk and Yager, and Kacprzyk, Yager and Zadrożny. Our main interest is in the summarization of trends characterized by: dynamics of change, duration and variability. To define the dynamic of change of the time series we propose to use for a preprocessing of data a SOM (self-organizing maps) learned with a LVQ (Learning Vector Quantization) algorithm, and then our approach for linguistic summaries of trends.

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Author information

Authors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk, Anna Wilbik & Sławomir Zadrożny

  2. Warsaw Information Technology (WIT), ul. Newelska 6, 01-447, Warsaw, Poland

    Sławomir Zadrożny

Authors
  1. Janusz Kacprzyk
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  2. Anna Wilbik
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  3. Sławomir Zadrożny
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Editor information

Editors and Affiliations

  1. School of Electrical and Computer Engineering, Image, Video and Multimedia Systems Laboratory, National Technical University of Athens, 157 80, Zographou, GR, Greece

    Stefanos Kollias

  2. Department of Electrical and Computer Engineering, National Technical University of Athens, 15780, Zographou, Greece

    Andreas Stafylopatis

  3. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  4. Adaptive Informatics Research Centre, Helsinki University of Technology, P.O. Box 5400, 02015, HUT, Finland

    Erkki Oja

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© 2006 Springer-Verlag Berlin Heidelberg

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Kacprzyk, J., Wilbik, A., Zadrożny, S. (2006). A Linguistic Approach to a Human-Consistent Summarization of Time Series Using a SOM Learned with a LVQ-Type Algorithm. In: Kollias, S., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840930_18

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  • DOI: https://doi.org/10.1007/11840930_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38871-5

  • Online ISBN: 978-3-540-38873-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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