A method for heuristic fuzzy modeling in noisy environment

2010 IEEE International Conference on Intelligent Systems, IS 2010 - Proceedings

Volumn , Issue , 2010, Pages 468-473

  Riid, Andri ^a   Rüstern, Ennu ^a  

^a TALLINN UNIVERSITY OF TECHNOLOGY   (Estonia)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION PROPERTIES; AUTOMATIC ALGORITHMS; BOX-JENKINS; CONTROL METHODOLOGY; DATA SETS; ESSENTIAL CHARACTERISTIC; FED-BATCH FERMENTATION; FUZZY MODEL IDENTIFICATION; FUZZY MODELING; MODELING TASK; NOISY ENVIRONMENT; WORKING PRINCIPLES;

FERMENTATION; HEURISTIC METHODS; INTELLIGENT SYSTEMS;

APPROXIMATION ALGORITHMS;

EID: 77957830929     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IS.2010.5548337     Document Type: Conference Paper

References (26)

1. T. Takagi and M. Sugeno, "Fuzzy identification of systems and its applications to modeling and control," IEEE Trans. Systems Man and Cybern., vol. 15, pp. 116-132, 1985. (Pubitemid 15111870)
2. J. Casillas, O. Cordon, F. Herrera and L. Magdalena (Eds.), Inter-pretability Issues in Fuzzy Modeling, Springer, Berlin, 2003.
3. A. Riid and E. Rüstern, "Interpretability of Fuzzy Systems and Its Application to Process Control," Proc. IEEE Int. Conf. Fuzzy Systems, London, 6 pp., 2007.
4. J.-S. R. Jang, C.-T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Prentice Hall, Upper Saddle River, 1996.
5. A. Riid and E. Rüstern, "Heuro-Fuzzy Extraction of Interpretable Fuzzy Rules from Data," Proc. IEEE Int. Conf. Syst., Man, Cybernetics, The Hague, 2266-2271, 2004. (Pubitemid 40408501)
6. Y. Nakoula, S. Galichet, and L. Foulloy, "Simultaneous Learning of Rules and Linguistic Terms," Proc. 5th IEEE Int. Conf. Fuzzy Systems, New Orleans, pp. 1743-1749, 1996.
7. K. Nozaki, H. Ishibuchi and H. Tanaka, "A simple but powerful heuristic method for generating fuzzy rules from numerical data," Fuzzy Sets and Systems, vol. 65, pp. 251-270, 1997. (Pubitemid 127683579)
8. A. Riid and E. Rüstern, "Transparent fuzzy systems and modeling with transparency protection,'" Proc. IFAC Symp. on Artificial Intelligence in Real Time Control, Budapest, pp. 229-234, 2000.
9. B. Kosko, "Optimal Fuzzy Rules Cover Extrema," Int. J. of Intelligent Systems, vol. 10, no. 2, pp. 249-255, 1995.
10. J. Abonyi, Fuzzy Model Identification for Control, Birkhauser, Boston, 2003
11. J. E. Box and G. M. Jenkins, Time Series Analysis, Forecasting and Control, San Francisco, Holden Day, 1970.
12. R. M. Tong, "Synthesis of Fuzzy Models For Industrial Processes: Some Recent Results," Int. J. General Syst., vol. 4, pp. 143-162, 1978.
13. W. Pedrycz, "An identification algorithm in fuzzy relational systems," Fuzzy Sets and Systems, vol. 13, pp. 153-167, 1984. (Pubitemid 14604942)
14. C. W. Xu and Y. Z. Lu, "Fuzzy model Identification and self-learning for dynamic systems," IEEE Trans. Syst. Man and Cyber., vol. 17, pp. 683-689, 1987. (Pubitemid 17650829)
15. M. Sugeno and K. Tanaka, "Successive Identification of a Fuzzy Model and its Application to Prediction of a Complex System," Fuzzy Sets and Systems, vol. 42, pp. 315-334, 1991.
16. L. Wang and R. Langari, "Complex Systems Modeling via Fuzzy Logic," IEEE Trans. on Syst., Man, and Cybernetics, vol. 26, no. 1, pp. 100-106, 1996. (Pubitemid 126780578)
17. M. Sugeno and T. Yasukawa, "A fuzzy-logic-based approach to qualitative modeling," IEEE Trans. Fuzzy Syst., vol. 1, no. 1, pp. 7-31, 1993.
18. M. S. Kim%, C. H. Kim and J. J. Lee, "Evolving compact and interpretable Takagi-Sugeno fuzzy models with a new encoding scheme," IEEE Trans. Syst. Man Cybernet B: Cybernet., vol. 36, no. 5, pp. 1006-1023, 2006.
19. Y. Lin and G. A. Cunningham, "A new approach to fuzzy-neural system modeling," IEEE Trans. Fuzzy Syst., vol. 3, no. 2, pp. 190-197, 1995.
20. J. Nie, "Constructing fuzzy model by self-organizing counterpropa-gation network," IEEE Trans. Syst. Man Cybernet. Vol. 25, no. 6, pp. 963-970, 1995.
21. A. Riid and E. Rüstern, "Interpretability Improvement of Fuzzy Systems: Reducing the Number of Unique Singletons in Zeroth order Takagi-Sugeno Systems," submitted for IEEE Int. Conf Fuzzy Systems, 2010.
22. S. L. Chiu, "Fuzzy Model Identification Based on Cluster Estimation," Journal of Intelligent and Fuzzy Systems, Vol. 2, pp. 267-278, 1994.
23. W. Faraq and A. Tawfik, "On Fuzzy Model Identification and the Gas Furnace Data," Proc. IASTED Int. Conf. Intelligent Systems and Control, Honolulu, pp. 210-214, 2000.
24. R. Leigh, "Fed-batch fermentation process modelling and control competition," Trans. Inst. MC, vol. 20, no. 1, pp. 3-4, 1998.
25. A. Riid and E. Rüstern, "Extracting and Exploiting Linguistic Information from a Fuzzy Process Model," in J. A. Tenreiro Machado, B. Patkai and I. J. Rudas (Eds.), Intelligent Engineering Systems and Computational Cybernetics, Springer-Verlag, pp. 95-105, 2009.
26. A. Riid and E. Rüstern, "Automatic Linguistic Inversion of a Fuzzy Model for Fed-Batch Fermentation Control," Proc. Int. Conf. Intelligent Engineering Systems, London, pp. 129-134, 2006. (Pubitemid 47130944)