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Aggregation Functions, Similarity and Fuzzy Measures

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Aggregation Functions in Theory and in Practice (AGOP 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 581))

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Abstract

We propose a new method for constructing fuzzy measures. This method is based on a fixed aggregation function A, similarity measure S and a vector \(\mathbf {x} \in [0,1]^n\). Some illustrative examples yielding parametric families of fuzzy measures are given, and some properties of our method are studied.

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Acknowledgement

This work was supported in part by Slovak Research and Development Agency under contract No. APVV–14–0013, the National Natural Science Foundation of China (Grants No. 11371332 and No. 11571106). Surajit Borkotokey acknowledges SAIA, Slovakia for providing him a scholarship under the National Scholarship Programme and the Department of Mathematics, STU, Bratislava for the hospitality received during January–March 2017.

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Authors and Affiliations

  1. Dibrugarh University, Dibrugarh, 786004, Assam, India

    Surajit Borkotokey

  2. Faculty of Civil Engineering, Slovak University of Technology, Radlinského 11, 810 05, Bratislava, Slovakia

    Magdaléna Komorníková & Radko Mesiar

  3. School of Science, Communication University of China, Beijing, 100024, China

    Jun Li

Authors
  1. Surajit Borkotokey
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  2. Magdaléna Komorníková
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  3. Jun Li
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  4. Radko Mesiar
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Corresponding author

Correspondence to Jun Li .

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Editors and Affiliations

  1. School of Informatics, University of Skövde, Skövde, Sweden

    Vicenç Torra

  2. Department of Mathematics and Descriptive Geometry, Slovak University of Technology, Bratislava, Slovakia

    Radko Mesiar

  3. KERMIT Research Unit Knowledge-based Systems, Ghent University, Ghent, Belgium

    Bernard De Baets

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Borkotokey, S., Komorníková, M., Li, J., Mesiar, R. (2018). Aggregation Functions, Similarity and Fuzzy Measures. In: Torra, V., Mesiar, R., Baets, B. (eds) Aggregation Functions in Theory and in Practice. AGOP 2017. Advances in Intelligent Systems and Computing, vol 581. Springer, Cham. https://doi.org/10.1007/978-3-319-59306-7_23

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  • DOI: https://doi.org/10.1007/978-3-319-59306-7_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59305-0

  • Online ISBN: 978-3-319-59306-7

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