Linear Fuzzy Regressions versus Power Fuzzy Regressions

Under the current conditions, the input data (values of the point cloud coordinates) necessary to achieve correlations and regressions between two variables representing two economic indicators are highly uncertain. However, by consulting a consistent number of specialists (a minimum of 3), by order...

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Détails bibliographiques
Auteur principal: Ovidiu Gherasim
Format: Article
Langue:English
Publié: Ovidius University Press 2021-01-01
Collection:Ovidius University Annals: Economic Sciences Series
Sujets:
Accès en ligne:https://stec.univ-ovidius.ro/html/anale/RO/2021-2/Section%203/15.pdf
Description
Résumé:Under the current conditions, the input data (values of the point cloud coordinates) necessary to achieve correlations and regressions between two variables representing two economic indicators are highly uncertain. However, by consulting a consistent number of specialists (a minimum of 3), by ordering and grouping the values obtained from them in 3 groups we can obtain, as arithmetic mean of the groups, modeling of the input data with triangular fuzzy numbers. In the article we presented the working method for obtaining linear fuzzy regressions and power fuzzy regressions then we compared the two types of fuzzy regressions by calculating the associated correlation coefficients.
ISSN:2393-3127