Sensitivity analysis of the weighted generalized mean aggregation operator and its application to fuzzy signatures

Harmati, István; Bukovics, Ádám; Kóczy, László T.

doi:10.1109/fuzz-ieee.2014.6891814

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Cited by 6 publications

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“…In this article we assume that all the operators applied on membership values in the signature are from the class of weighted generalized mean aggregation operators (WGMs). A similar question was investigated in [8], but for different cases and by different mathematical tools.…”

Section: Introductionmentioning

confidence: 99%

Minkowski’s Inequality Based Sensitivity Analysis of Fuzzy Signatures

Harmati

Bukovics

Kóczy

2016

Journal of Artificial Intelligence and Soft Computing Research

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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.

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Section: Introductionmentioning

confidence: 99%