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Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy etc. Methods and Their Applications pp 121–136Cite as

How to Enhance, Use and Understand Fuzzy Relational Compositions

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 835))

Abstract

This article focuses on fuzzy relational compositions, that unquestionably played a crucial role in fundamentals of fuzzy mathematics since the very beginning of their development. We follow the original works aiming at medical diagnosis, where the compositions were actually used for a sort of classification and/or pattern recognition based on expert knowledge stored in the used fuzzy relations. We provide readers with short repetition of theoretical foundations and two recent extensions of the compositions and then, we introduce how they may be combined together. No matter the huge potential of the original compositions and their extensions, if the features are constructed in a certain specific yet very natural way, some limitations for the applicability may be encountered anyhow. This will be demonstrated on a real classification example from biology. The proposed combinations of extensions will be also experimentally evaluated and they will show the potential for further improvements.

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Author information

Authors and Affiliations

  1. Institute for Research and Applications of Fuzzy Modeling, CE IT4Innovations, University of Ostrava, 30. dubna 22, 701 03, Ostrava, Czech Republic

    Nhung Cao, Martin Štěpnička & Michal Burda

  2. Department of Biology and Ecology, University of Ostrava, Chittusiho 10, 710 00, Ostrava, Czech Republic

    Aleš Dolný

Authors
  1. Nhung Cao
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  2. Martin Štěpnička
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  3. Michal Burda
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  4. Aleš Dolný
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Corresponding author

Correspondence to Martin Štěpnička .

Editor information

Editors and Affiliations

  1. Department of Teacher Education, University of Texas at El Paso, El Paso, TX, USA

    Olga Kosheleva

  2. Institute of Computational Technologies SB RAS, Novosibirsk, Russia

    Sergey P. Shary

  3. Johns Creek, GA, USA

    Gang Xiang

  4. Deptartment of Informatics, The State Russian Museum, Saint Petersburg, Russia

    Roman Zapatrin

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Cao, N., Štěpnička, M., Burda, M., Dolný, A. (2020). How to Enhance, Use and Understand Fuzzy Relational Compositions. In: Kosheleva, O., Shary, S., Xiang, G., Zapatrin, R. (eds) Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy etc. Methods and Their Applications. Studies in Computational Intelligence, vol 835. Springer, Cham. https://doi.org/10.1007/978-3-030-31041-7_7

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