Regularized adaptation of fuzzy inference systems. Modelling the opinion of a medical expert about physical fitness: An application

Fuzzy Optimization and Decision Making

Volumn 2, Issue 4, 2003, Pages 317-336

  Kumar, Mohit ^a   Stoll, Regina ^a   Stoll, Norbert ^a  

^a UNIVERSITY OF ROSTOCK   (Germany)

Author keywords

Fuzzy approximation; Generalized predictive control; Ill posed; Inverse control; Model identification; Nonlinear least squares; Regularization

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; BOUNDARY VALUE PROBLEMS; INVERSE PROBLEMS; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; MEMBERSHIP FUNCTIONS; OPTIMIZATION; PARAMETER ESTIMATION; ROBUSTNESS (CONTROL SYSTEMS);

FUZZY APPROXIMATION; GENERALIZED PREDICTIVE CONTROL (GPC); ILL-POSED; INVERSE CONTROL; MODEL IDENTIFICATION; NONLINEAR LEAST SQUARES; REGULARIZATION;

FUZZY SETS;

EID: 3543138233     PISSN: 15684539     EISSN: None     Source Type: Journal    
DOI: 10.1023/B:FODM.0000003952.07461.ed     Document Type: Article

References (17)

1. Babuska, R. (2000). "Construction of Fuzzy Systems-Interplay Between Precision and Transparency," In Proc. ESIT 2000. Aachen, 445-452.
2. Binder, A., H. W. Engl, C. W. Groetsch, A. Neubauer and O. Scherzer. (1994). "Weakly Closed Nonlinear Operators and Parameter Identification in Parabolic Equations by Tikhonov Regularization," Appl. Anal. 55, 215-234.
3. Bodenhofer, U. and P. Bauer. (2000). "Towards an Axiomatic Treatment of Interpretability," In Proc. IIZUKA2000. lizuka, 334-339 (October).
4. Burger, M., J. Haslinger and U. Bodenhofer. (2000). "Regularized Optimization of Fuzzy Controllers," Technical Report SCCH-TR-0056, Software Competence Center Hagenberg.
5. Burger, M., H. W. Engl, J. Haslinger, and U. Bodenhofer. (2002). "Regularized Data-Driven Construction of Fuzzy Controllers," J. Inverse and Ill-posed Problems 10, 319-344.
6. Engl, H. W., K. Kunisch, and A. Neubauer. (1989). "Convergence Rates for Tikhonov Regularization of Nonlinear Ill-Posed Problems" Inverse Problems 5, 523-540.
7. Engl, H. W., M. Hankc, and A. Neubauer. (1996). Regularization of Inverse Problems. Dordrecht: Kluwer Academic Publishers.
8. Espinosa, J. and J. Vandewalle. (2000). "Constructing Fuzzy Models with Linguistic Integrity from Numerical Data-AFRELI Algorithm," IEEE Trans. Fuzzy Systems 8(5), 591-600 (October).
9. Jang. J.-S. R., C.-T. Sun and E. Mizutani. (1997). Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence. Prentice Hall, Chapter 12, 345-360.
10. Lawson, C. L. and R. J. Hanson. (1995). Solving Least squares Problems. Philadelphia: SIAM Publications.
11. Nauck, D. and R. Kruse. (1999). "Obtaining Interpretable Fuzzy Classification Rules from Medical Data," Artificial Intelligence in Medicine 16, 149-169.
12. Setnes, M., R. Babuka, and H. B. Verbruggen. (1998). "Rule-Based Modeling: Precision and Transparency," IEEE Trans. Syst. Man Cybern.Part C: Applications and Reviews 28, 165-69.
13. Takagi, T. and M. Sugeno. (1985). "Fuzzy Identification of Systems and Its Applications to Modeling and Control," IEEE Trans. Syst. Man Cybern 15(1), 116-132.
14. Väinämö, K., S. Nissilä, T. Mäkikallio, M. Tulppo and J. Röning. (1996). "Artificial Neural Network for Aerobic Fitness Approximation," International Conference on Neural Networks (ICNN96). Washington DC, USA (June 3-6).
15. Väinämö, K., T. Mäkikallio. M. Tulppo and. J. Röning. (1998). "A Neuro-Fuzzy Approach to Aerobic Fitness Classification: A Multistructure Solution to the Context-Sensitivc Feature Selection Problem," Proc. WCCI '98. Anchorage, Alaska, USA, 797-802 (May 4-9).
16. Widrow, B. and M. A. Lehr. (1990). "30 Years of Adaptive Neural Networks: Perceptron, Madline and Backpropagation," Proceeding of the IEEE 78(9), 1415-1422.
17. Zadeh, L. A. (1973). "Outline of a New Approach to the Analysis of Complex Systems and Decision Processes," IEEE Trans. Syst. Man Cybern 3(1), 28-44.