Robust regression and outlier detection
Robust regression and outlier detection
Information Sciences: an International Journal
Characterization and detection of noise in clustering
Pattern Recognition Letters
Multiobjective fuzzy linear regression analysis for fuzzy input-output data
Fuzzy Sets and Systems
Approximation of functional relationships to fuzzy observations
Fuzzy Sets and Systems
On a class of fuzzy classification maximum likelihood procedures
Fuzzy Sets and Systems
Exponential possibility regression analysis
Fuzzy Sets and Systems - Special issue on fuzzy information processing
On fuzzy clustering of directional data
Fuzzy Sets and Systems
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
On cluster-wise fuzzy regression analysis
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust clustering methods: a unified view
IEEE Transactions on Fuzzy Systems
Fuzzy least-squares algorithms for interactive fuzzy linear regression models
Fuzzy Sets and Systems - Theme: Modeling and learning
Fuzzy linear regression analysis from the point of view risk
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
A novel fuzzy regression approach on managing target cash balance for construction firms
MS'06 Proceedings of the 17th IASTED international conference on Modelling and simulation
Fuzzy nonparametric regression based on local linear smoothing technique
Information Sciences: an International Journal
Asymptotic properties of least squares estimation with fuzzy observations
Information Sciences: an International Journal
An enhanced fuzzy linear regression model with more flexible spreads
Fuzzy Sets and Systems
Reduction to least-squares estimates in multiple fuzzy regression analysis
IEEE Transactions on Fuzzy Systems
Managing Target Cash Balance in Construction Firms Using Novel Fuzzy Regression Approach
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Fuzzy process control: construction of control charts with fuzzy numbers
Fuzzy Sets and Systems
An improved Takagi-Sugeno fuzzy model with multidimensional fuzzy sets
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - FUZZYSS’2009
Fuzzy least-absolutes regression using shape preserving operations
Information Sciences: an International Journal
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A fuzzy regression model is used in evaluating the functional relationship between the dependent and independent variables in a fuzzy environment. Most fuzzy regression models are considered to be fuzzy outputs and parameters but non-fuzzy (crisp) inputs. In general, there are two approaches in the analysis of fuzzy regression models: linear-programming-based methods and fuzzy least-squares methods. In 1992, Sakawa and Yano considered fuzzy linear regression models with fuzzy outputs, fuzzy parameters and also fuzzy inputs. They formulated multiobjective programming methods for the model estimation along with a linear-programming-based approach. In this paper, two estimation methods along with a fuzzy least-squares approach are proposed. These proposed methods can be effectively used for the parameter estimation. Comparisons are also made between them.