A weighted goal programming approach to fuzzy linear regression with crisp inputs and type-2 fuzzy outputs

DOI10.1007/s00500-014-1328-3zbMath1386.62024OpenAlexW1988826918MaRDI QIDQ1708727

E. Hosseinzadeh, Mohsen Arefi, Hassan Hassanpour

Publication date: 26 March 2018

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

Full work available at URL: https://doi.org/10.1007/s00500-014-1328-3

zbMATH Keywords

uncertaintygoal programminglinear regressiontype-2 fuzzy setlinguistic variabletype-2 fuzzy number

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Multi-objective and goal programming (90C29) Fuzziness, and linear inference and regression (62J86)

Related Items (7)

A parametric recurrent neural network scheme for solving a class of fuzzy regression models with some real-world applications ⋮ Estimating the parameters of fuzzy linear regression model with crisp inputs and Gaussian fuzzy outputs: a goal programming approach ⋮ A decision-making computational methodology for a class of type-2 fuzzy intervals: an interval-based approach ⋮ Prediction of retinopathy in diabetic patients using type-2 fuzzy regression model ⋮ A weighted goal programming approach to estimate the linear regression model in full quasi type-2 fuzzy environment ⋮ Clustering regression based on interval-valued fuzzy outputs and interval-valued fuzzy parameters ⋮ Quantile fuzzy regression based on fuzzy outputs and fuzzy parameters

Uses Software

• LINDO
• LINGO

Cites Work

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