Multiple regression with fuzzy data

Fuzzy Sets and Systems

Volumn 158, Issue 19, 2007, Pages 2169-2188

  Bargiela, Andrzej ^a   Pedrycz, Witold ^b   Nakashima, Tomoharu ^c  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^b UNIVERSITY OF ALBERTA   (Canada)

^c Osaka Prefecture University   (Japan)

Author keywords

Fuzzy C means (FCM); Fuzzy data; Gradient descent; Multiple regression

Indexed keywords

ALGORITHMS; ITERATIVE METHODS; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; OPTIMIZATION; PROBLEM SOLVING; REGRESSION ANALYSIS;

FUZZY C-MEANS (FCM); FUZZY DATA; FUZZY VARIABLES; GRADIENT DESCENT; MULTIPLE REGRESSION;

FUZZY SETS;

EID: 34547491789     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.fss.2007.04.011     Document Type: Article

References (24)

1. de Andrés Sánchez J., and Gómez A.T. Estimating a fuzzy term structure of interest rates using fuzzy regression techniques. European J. Oper. Res. 154 3 (2004) 804-818
2. Bardossy A. Note on fuzzy regression. Fuzzy Sets and Systems 37 (1990) 65-75
3. Bardossy A., Bogardi I., and Duckstein L. Fuzzy regression in hydrology. Water Resources Res. 26 (1990) 1497-1508
4. Bargiela A., and Pedrycz W. Granular Computing (2002), Kluwer Academic Publishers, Dordrecht
5. Bargiela A., and Pedrycz W. Recursive information granulation. IEEE Trans. Systems Man Cybernet. 33 1 (2003) 96-112
6. Cheng C.B., and Lee E.S. Fuzzy regression with radial basis function network. Fuzzy Sets and Systems 119 2 (2001) 291-301
7. Diamond P. Fuzzy least squares. Inform. Sci. 46 (1988) 141-157
8. Diamond P. Least squares and maximum likelihood regression for fuzzy linear models. In: Kacprzyk J., and Fedrizzi M. (Eds). Fuzzy Regression Analysis (1992) 137-151
9. Diamond P., and Koerner R. Extended fuzzy linear models and least squares estimates. Comput. Math. Appl. 33 9 (1997) 15-32
10. P. Grzegorzewski, E. Mrowka, Regression analysis with fuzzy data, in: P. Grzegorzewski, M. Krawczak, S. Zadrozny (Eds.), Soft Computing: Tools, Techniques and Applications, 2004.
11. Hojati M., Bector C.R., and Smimou K. A simple method for computation of fuzzy linear regression. European J. Oper. Res. 166 1 (2005) 172-184
12. Hong D.H., and Hwang C. Extended fuzzy regression models using regularization method. Inform. Sci. 164 1-4 (2004) 31-46
13. Kacprzyk J., and Fedrizzi M. Fuzzy regression analysis (1992), Omnitech Press, Physica-Verlag, Warsaw Heildelberg
14. Kao C., and Chyu C.L. Least-squares estimates in fuzzy regression analysis. European J. Oper. Res. 148 2 (2003) 426-435
15. Koerner R., and Nather W. Linear regression with random fuzzy variables. Inform. Sci. 109 (1998) 95-118
16. Nasrabadi M.N., and Nasrabadi E. A mathematical-programming approach to fuzzy linear regression analysis. Appl. Math. Comput. 155 3 (2004) 873-881
17. Pedrycz W., and Gomide F. An Introduction to Fuzzy Sets: Analysis and Design (1998), MIT Press, Cambridge, MA
18. Savic D.A., and Pedrycz W. Evaluation of fuzzy linear regression models. Fuzzy Sets and Systems 39 (1991) 51-63
19. Tanaka H., Uegima S., and Asai K. Linear regression analysis with fuzzy model. IEEE Trans. Systems Man Cybernet. 12 (1982) 903-907
20. Xue Y., Kim I.S., Son J.S., Park C.E., Kim H.H., Sung B.S., Kim I.J., Kim H.J., and Kang B.Y. Fuzzy regression method for prediction and control the bead width in the robotic arc-welding process. J. Mat. Process. Technol. 164-165 (2005) 1134-1139
21. Yen K.K., Ghoshray S., and Roig G. A linear regression model using triangular fuzzy number coefficients. Fuzzy Sets and Systems 106 (1999) 167-177
22. Zadeh L.A. Fuzzy sets. Inform. and Control 8 (1965) 338-353
23. Zadeh L.A. Fuzzy sets and information granularity. In: Gupta M.M., Ragade R.K., and Yager R.R. (Eds). Advances in Fuzzy Set Theory and Applications (1979), North Holland, Amsterdam 3-18
24. Zadeh L.A. Fuzzy logic = computing with words. IEEE Trans. Fuzzy Systems 4 2 (1996) 103-111