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Adaptive Fuzzy Clustering of Multivariate Short Time Series with Unevenly Distributed Observations Based on Matrix Neuro-Fuzzy Self-organizing Network

  • Galina Setlak
  • Yevgeniy BodyanskiyEmail author
  • Iryna Pliss
  • Olena Vynokurova
  • Dmytro Peleshko
  • Illya Kobylin
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 643)

Abstract

In the paper the method of fuzzy clustering task for multivariate short time series with unevenly distributed observations is proposed. Proposed method allows to process the time series both in batch mode and sequential on-line mode. In the first case we can use the matrix modification of fuzzy C-means method, and in second case we can use the matrix modification of neuro-fuzzy network by T. Kohonen, which is learned using the rule “Winner takes more”. Proposed fuzzy clustering algorithms are enough simple in computational implementation and can be used for solving of wide class of Big Data and Data Stream Mining problems. The effectiveness of proposed approach is confirmed by many experiments based on real data sets.

Keywords

Adaptive fuzzy clustering Multivariate short time series Unevenly distributed observations Matrix neuro-fuzzy self-organizing network 

References

  1. 1.
    Liao, T.W.: Clustering of time series data-a survey. Pattern Recogn. 38(11), 1857–1874 (2005). doi: 10.1016/j.patcog.2005.01.025 CrossRefzbMATHGoogle Scholar
  2. 2.
    Mitsa, T.: Temporal Data Mining. CRC Press, Boca Raton (2010)CrossRefzbMATHGoogle Scholar
  3. 3.
    Aggarwal, C.C., Reddy, C.K.: Data Clustering. Algorithms, and Applications. CRC Press, Boca Raton (2014)zbMATHGoogle Scholar
  4. 4.
    Aggarwal, C.C.: Data Mining. Springer, New York (2015)CrossRefzbMATHGoogle Scholar
  5. 5.
    Möller-Levet, C.S., Klawonn, F., Cho, K.-H., Wolkenhauer, O.: Fuzzy clustering of short time series with unevenly distributed sampling points. Lecture Notes in Computers Science, vol. 2810, pp. 330–340. Springer, Heidelberg (2003). doi: 10.1007/978-3-540-45231-7_31
  6. 6.
    Cruz, L.P., Vieira, S.M., Vinga, S.: Fuzzy clustering for incomplete short time series data. Lecture Notes in Artificial Intelligence, vol. 9273, pp. 353–359. Springer Int. Publishing, Switzerland (2015). doi: 10.1007/978-3-319-23485-4_36
  7. 7.
    Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York (1981)CrossRefzbMATHGoogle Scholar
  8. 8.
    Höppner, F., Klawonn, F., Kruse, R., Runkler, T.: Fuzzy Clustering Analysis: Methods for Classification, Data Analysis, and Image Recognition. Wiley, Chichester (1999)zbMATHGoogle Scholar
  9. 9.
    Bifet, A.: Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams. IOS Press, Amsterdam (2010)zbMATHGoogle Scholar
  10. 10.
    Bodyanskiy, Y., Skuratov, M., Volkova, V.: Adaptive matrix fuzzy c-means clustering. In: 19th East-West Fuzzy-Colloquium, pp. 96–103. HS, Zittau-Görlitz (2012)Google Scholar
  11. 11.
    Kohonen, T.: Self-Organizing Maps. Springer, Berlin (1995)CrossRefzbMATHGoogle Scholar
  12. 12.
    Haykin, S.: Neural Networks. A Comprehensive Foundation. Prentice Hall, Upper Saddle River (1999)zbMATHGoogle Scholar
  13. 13.
    Bodyanskiy, Y., Skuratov, M., Volkova, V.: Matrix neuro-fuzzy self-organizing clustering network. Comput. Sci. Inf. Technol. Manag. Sci. 49, 54–58 (2011). doi: 10.2478/v10143-011-0042-1 Google Scholar
  14. 14.
    Deoras, A.: Electricity load forecasting using neural networks. In: Electricity Load and Price Forecasting Webinar Case Study (2011). https://www.mathworks.com/matlabcentral/fileexchange/28684-electricity-load-and-price-forecasting-webinar-case-study?s_tid=srchtitle

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Galina Setlak
    • 1
  • Yevgeniy Bodyanskiy
    • 2
    Email author
  • Iryna Pliss
    • 2
  • Olena Vynokurova
    • 2
  • Dmytro Peleshko
    • 3
  • Illya Kobylin
    • 2
  1. 1.Rzeszow University of TechnologyRzeszowPoland
  2. 2.Kharkiv National University of Radio ElectronicsKharkivUkraine
  3. 3.University “IT Step Academy”LvivUkraine

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