Quantile fuzzy regression based on fuzzy outputs and fuzzy parameters

DOI10.1007/s00500-019-04424-2zbMath1436.62366OpenAlexW2982587061WikidataQ126860959 ScholiaQ126860959MaRDI QIDQ780249

Mohsen Arefi

Publication date: 15 July 2020

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-019-04424-2

zbMATH Keywords

loss functionfuzzy numbergoodness of fitfuzzy parameterquantile fuzzy regression

Mathematics Subject Classification ID

Fuzziness, and linear inference and regression (62J86)

Related Items (7)

A robust least squares fuzzy regression model based on kernel function ⋮ A parametric recurrent neural network scheme for solving a class of fuzzy regression models with some real-world applications ⋮ A general approach to fuzzy regression models based on different loss functions ⋮ A fuzzy empirical quantile-based regression model based on triangular fuzzy numbers ⋮ A generalized bridge regression in fuzzy environment and its numerical solution by a capable recurrent neural network ⋮ Interval type-2 fuzzy least-squares estimation to formulate a regression model based on a new outlier detection method using a new distance ⋮ OWA fuzzy regression

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