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Journal of Artificial Intelligence and Soft Computing Research

The Journal of Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology

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Minkowski’s Inequality Based Sensitivity Analysis of Fuzzy Signatures

István Á. Harmati
  • Corresponding author
  • Department of Mathematics and Computational Sciences Széchenyi István University, Egyetem tér 1, 9026 Győr, Hungary
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/ Ádám Bukovics
  • Department of Structural and Geotechnical Engineering Széchenyi István University, Egyetem tér 1, 9026 Győr, Hungary
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/ László T. Kóczy
  • Department of Automation Széchenyi István University, Egyetem tér 1, 9026 Győr, Hungary Department of Telecommunications and Media Informatics Budapest University of Technology and Economics, Budapest, Hungary
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Published Online: 2016-08-10 | DOI: https://doi.org/10.1515/jaiscr-2016-0016


Fuzzy signatures were introduced as special tools to describe and handle complex systems without their detailed mathematical models. The input parameters of these systems naturally have uncertainties, due to human activities or lack of precise data. These uncertainties influence the final conclusion or decision about the system. In this paper we discuss the sensitivity of the weigthed general mean aggregation operator to the uncertainty of the input values, then we analyse the sensitivity of fuzzy signatures equipped with these aggregation operators. Finally, we apply our results to a fuzzy signature used in civil enginnering.

Keywords: aggregation operators; generalized mean; sensitivity analysis; fuzzy signatures; building diagnostics


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About the article

Published Online: 2016-08-10

Published in Print: 2016-10-01

Citation Information: Journal of Artificial Intelligence and Soft Computing Research, Volume 6, Issue 4, Pages 219–229, ISSN (Online) 2083-2567, DOI: https://doi.org/10.1515/jaiscr-2016-0016.

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© 2016. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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