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Fuzzy Metric Approach to Aggregation of Risk Levels

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Computational Intelligence and Mathematics for Tackling Complex Problems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 819))

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Abstract

In this paper we propose a special construction of a general aggregation operator. The construction allows to aggregate fuzzy sets taking into account the distance between elements of the universe. We consider the case when fuzzy sets to be aggregated represent the risk level evaluation by several experts. We describe how the proposed construction could be applied for risk level assessment in the case when a strong fuzzy metric is used to characterize the similarity of objects under evaluation.

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Author information

Authors and Affiliations

  1. Institute of Mathematics and Computer Science, Riga, Latvia

    Svetlana Asmuss

  2. Department of Mathematics, University of Latvia, Riga, Latvia

    Svetlana Asmuss & Pavels Orlovs

Authors
  1. Svetlana Asmuss
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  2. Pavels Orlovs
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Corresponding author

Correspondence to Svetlana Asmuss .

Editor information

Editors and Affiliations

  1. Faculty of Engineering Sciences, Széchenyi István University, Gyõr, Hungary

    László T Kóczy

  2. Science Faculty, Department of Mathematics, University of Cádiz, Cádiz, Spain

    Jesús Medina-Moreno

  3. Faculty of Economic and Business Sciences, Department of Mathematics, University of Cádiz, Cádiz, Spain

    Eloísa Ramírez-Poussa

  4. Institute of Mathematics and Computer Science, University of Latvia, Riga, Latvia

    Alexander Å ostak

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Asmuss, S., Orlovs, P. (2020). Fuzzy Metric Approach to Aggregation of Risk Levels. In: Kóczy, L., Medina-Moreno, J., Ramírez-Poussa, E., Šostak, A. (eds) Computational Intelligence and Mathematics for Tackling Complex Problems. Studies in Computational Intelligence, vol 819. Springer, Cham. https://doi.org/10.1007/978-3-030-16024-1_22

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