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Z-Number Clustering Based on General Type-2 Fuzzy Sets

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13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018 (ICAFS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 896))

Abstract

Clustering is a convenient tool to extract or summarize information from large data sets. Data sets collected by modern information systems are constantly increasing in size. These data sets may include imprecise and partially reliable information. Usually this uncertainty is both probabilistic and fuzzy. Unfortunately, up-to-date there is almost no research on clustering which takes into account a synergy of both probability and fuzziness in produced information. In this paper, we first suggest an approach to clustering large data sets with probabilistic and fuzzy uncertainties. This approach is based on relationship of general Type-2 Fuzzy and Z-number concepts. A numerical example is considered to demonstrate the validity of the proposed method.

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Author information

Authors and Affiliations

  1. Azerbaijan State Oil and Industry University, Baku, Azerbaijan

    Rafik Aliev

  2. SOCAR Midstream Operations, Baku, Azerbaijan

    Babek Guirimov

Authors
  1. Rafik Aliev
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  2. Babek Guirimov
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Corresponding author

Correspondence to Rafik Aliev .

Editor information

Editors and Affiliations

  1. Joint MBA Program, Azerbaijan State Oil and Industry University, Baku, Azerbaijan

    Rafik A. Aliev

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  4. Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA

    Mo. Jamshidi

  5. Department of Mechatronics, Near East University, Nicosia TRNC, Turkey

    Fahreddin M. Sadikoglu

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Aliev, R., Guirimov, B. (2019). Z-Number Clustering Based on General Type-2 Fuzzy Sets. In: Aliev, R., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Sadikoglu, F. (eds) 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018. ICAFS 2018. Advances in Intelligent Systems and Computing, vol 896. Springer, Cham. https://doi.org/10.1007/978-3-030-04164-9_37

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