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Mixture Functions Based on Deviation and Dissimilarity Functions

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New Trends in Aggregation Theory (AGOP 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 981))

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Abstract

Mixture functions represent a special class of weighted averaging functions with weights determined by continuous weighting functions which depend on the input values. If they are monotone increasing, they also belong to the important class of aggregation functions. Their construction can be based on minimization of special (weighted) penalty functions using dissimilarity function or based on zero value of the special (weighted) strictly increasing function using deviation functions.

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Acknowledgement

Jana Špirková has been supported by the project VEGA no. 1/0093/17 Identification of risk factors and their impact on products of the insurance and savings schemes.

Pavol Král’ has been supported by the project VEGA 1/0767/18 SMART model - a decision support tool in management of enterprises.

Author information

Authors and Affiliations

  1. Faculty of Economics, Matej Bel University, Tajovského 10, 975 90, Banská Bystrica, Slovakia

    Jana Špirková & Pavol Král’

Authors
  1. Jana Špirková
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  2. Pavol Král’
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Corresponding author

Correspondence to Jana Špirková .

Editor information

Editors and Affiliations

  1. Faculty of Science, Palacký University, Olomouc, Czech Republic

    Radomír Halaš

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

    Marek Gagolewski

  3. Slovak University of Technology, Bratislava, Slovakia

    Radko Mesiar

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Špirková, J., Král’, P. (2019). Mixture Functions Based on Deviation and Dissimilarity Functions. In: Halaš, R., Gagolewski, M., Mesiar, R. (eds) New Trends in Aggregation Theory. AGOP 2019. Advances in Intelligent Systems and Computing, vol 981. Springer, Cham. https://doi.org/10.1007/978-3-030-19494-9_24

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