Generating fuzzy models from deep knowledge: Robustness and interpretability issues

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3571 LNAI, Issue , 2005, Pages 600-612

  Guglielmann, Raffaella ^a   Ironi, Liliana ^b  

^a UNIVERSITY OF PAVIA   (Italy)

^b CNR   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

DATA REDUCTION; INFORMATION ANALYSIS; KNOWLEDGE ENGINEERING; KNOWLEDGE REPRESENTATION; PARAMETER ESTIMATION; PROBLEM SOLVING; ROBUSTNESS (CONTROL SYSTEMS);

FUZZY MODELS; INTERPRETABILITY ISSUES; QUALITATIVE REASONING; SYSTEM DYNAMICS;

FUZZY SETS;

EID: 26944449655     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11518655_51     Document Type: Conference Paper

References (21)

1. Jang, J.: Anfis: Adaptive network based fuzzy inference system. IEEE Trans. on Systems, Man and Cybernetics 23 (1993) 665-685
2. Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control. IEEE Trans. on Systems, Man and Cybernetics 15 (1985) 116-132
3. Wang, L., Mendel, J.: Generating fuzzy rules by learning from examples. IEEE Trans. on Systems, Man and Cybernetics 22 (1992) 1414-1427
4. Wang, L.: Adaptive Fuzzy Systems and Control: design and stability analysis. Englewood Cliff, NJ:Prentice-Hall, University of California at Berkeley (1994)
5. Bellazzi, R., Guglielmann, R., Irani, L.: How to improve fuzzy-neural system modeling by means of qualitative simulation. IEEE Trans. on Neural Network 11 (2000) 249-253
6. Bellazzi, R., Guglielmann, R., Ironi, L., Patrini, C.: A hybrid input-output approach to model metabolic systems: An application to intracellular thiamine kinetics. Journal of Biomedical Informatics 34 (2001) 221-248
7. Kuipers, B.J.: Qualitative Reasoning: modeling and simulation with incomplete knowledge. MIT Press, Cambridge MA (1994)
8. D'Ambrosio, B.: Qualitative process theory using linguistic variables. Springer, New-York (1989)
9. Kim, G., Fishwick, P.: A validation method using fuzzy simulation in an object oriented physical modeling framework. In: Proc. SPIE Aerosense Conference, Orlando, Florida (1998)
10. Shen, Q., Leitch, R.: Fuzzy qualitative simulation. IEEE Trans. on Systems, Man and Cybernetics 23 (1993) 1038-1061
11. Ljung, L.: System Identification - Theory for the User. Prentice-Hall, Englewood Cliffs (1987)
12. Mamdani, E.: Applications of fuzzy algorithms for simple dynamic plant. Proc. IEE 121 (1974) 1585-1588
13. Abe, S., Lan, M.: Fuzzy rules extraction directly from numerical data for function approximation. IEEE Trans. on Systems, Man and Cybernetics 25 (1995) 119-129
14. Horikawa, S., Furuhashi, T., Uchikawa, Y.: On fuzzy modeling using fuzzy neural networks with the back-propagation algorithm. IEEE Trans. on Neural Networks 3 (1992) 801-814
15. Pomares, H., Rojas, I., Gonzales, J., Prieto, A.: Structure identification in complete rule-based fuzzy systems. IEEE Trans. on Fuzzy Systems 10 (2002) 349-359
16. Bezdek, J.: Pattern recognition with fuzzy objective function algoritms. Plenum, New York (1981)
17. Sugeno, M., Yasukawa, T.: A fuzzy-logic based approach to qualitative modeling. IEEE Trans. on Fuzzy Systems 1 (1993) 7-31
18. Tikhonov, A., Arsenin, V.: Solutions of ill-posed problems. Winston, Washington DC (1977)
19. Jin, Y: Fuzzy modeling of high-dimensional systems: complexity reduction and interpretability improvement. IEEE Trans. on Fuzzy Systems 8 (2000) 212-221
20. Nocedal, J., Wright, S.J.: Numerical Optimization. Springer, New York (1999)
21. Zeng, X., Singh, M.: Approximation accuracy analysis of fuzzy systems as functions approximators. IEEE Trans. on Fuzzy Systems 4 (1996) 44-63