Dependency between degree of fit and input noise in fuzzy linear regression using non-symmet\-ric fuzzy triangular coefficients
From MaRDI portal
Publication:2458688
DOI10.1016/j.fss.2007.03.011zbMath1121.62064OpenAlexW2014145878MaRDI QIDQ2458688
Publication date: 2 November 2007
Published in: Fuzzy Sets and Systems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.fss.2007.03.011
Related Items (6)
On general form of fuzzy lines and its application in fuzzy line fitting ⋮ Unnamed Item ⋮ An exponential-type kernel robust regression model for interval-valued variables ⋮ From fuzzy regression to gradual regression: interval-based analysis and extensions ⋮ A variable spread fuzzy linear regression model with higher explanatory power and forecasting accuracy ⋮ A revisited approach to linear fuzzy regression using trapezoidal fuzzy intervals
Cites Work
- Evaluation of fuzzy linear regression models
- Identification of possibilistic linear systems by quadratic membership functions of fuzzy parameters
- Fuzzy data analysis by possibilistic linear models
- Possibilistic linear systems and their application to the linear regression model
- Multiobjective fuzzy linear regression analysis for fuzzy input-output data
- A linear regression model using triangular fuzzy number coefficients
- Support vector fuzzy regression machines
- Exponential possibility regression analysis
- Properties of certain fuzzy linear regression methods
- Theoretically optimal parameter choices for support vector regression machines with noisy input
- Linear Regression Analysis with Fuzzy Model
- A probabilistic framework for SVM regression and error bar estimation
This page was built for publication: Dependency between degree of fit and input noise in fuzzy linear regression using non-symmet\-ric fuzzy triangular coefficients
