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Aggregation Functions Based on Deviations

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations (IPMU 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 853))

Abstract

After recalling penalty and deviation based constructions of idempotent aggregation functions, we introduce the concept of a general deviation function and related construction of aggregation functions. Our approach is exemplified in some examples, illustrating the ability of our method to model possibly different aggregation attitudes in different coordinates of the aggregated score vectors.

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Acknowledgments

The support of the grants APVV-14-0013 and VEGA 1/0682/16 is kindly announced.

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Authors and Affiliations

  1. Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Radlinského 11, 810 05, Bratislava, Slovak Republic

    Marián Decký, Radko Mesiar & Andrea Stupňanová

Authors
  1. Marián Decký
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  2. Radko Mesiar
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  3. Andrea Stupňanová
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Corresponding author

Correspondence to Andrea Stupňanová .

Editor information

Editors and Affiliations

  1. Universidad de Cádiz, Cádiz, Cadiz, Spain

    Jesús Medina

  2. Universidad de Málaga, Málaga, Málaga, Spain

    Manuel Ojeda-Aciego

  3. Universidad de Granada, Granada, Spain

    José Luis Verdegay

  4. Universidad de Granada, Granada, Spain

    David A. Pelta

  5. Universidad de Málaga, Málaga, Málaga, Spain

    Inma P. Cabrera

  6. LIP6, Université Pierre et Marie Curie, CNRS, Paris, France

    Bernadette Bouchon-Meunier

  7. Iona College, New Rochelle, New York, USA

    Ronald R. Yager

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Decký, M., Mesiar, R., Stupňanová, A. (2018). Aggregation Functions Based on Deviations. In: Medina, J., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 853. Springer, Cham. https://doi.org/10.1007/978-3-319-91473-2_13

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  • DOI: https://doi.org/10.1007/978-3-319-91473-2_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91472-5

  • Online ISBN: 978-3-319-91473-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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