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Mixture Functions Based on Deviation and Dissimilarity Functions

  • Jana ŠpirkováEmail author
  • Pavol Král’
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 981)

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.

Notes

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.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of EconomicsMatej Bel UniversityBanská BystricaSlovakia

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