An integrated approach to intelligent modeling of industrial plants

Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA

Volumn 3, Issue , 2003, Pages 1527-1532

  Christova, Nikolinka ^a   Hadjiski, Mincho ^a   Vachkov, Gancho ^b   Stylios, Chrysostomos ^c  

^a UNIVERSITY OF CHEMICAL TECHNOLOGY AND METALLURGY   (Bulgaria)

^b KAGAWA UNIVERSITY   (Japan)

^c UNIVERSITY OF IOANNINA   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; AUTOMATION; ROBOTICS; SOFT COMPUTING;

COMPLEX INDUSTRIAL SYSTEMS; FUZZY COGNITIVE MAP; HIERARCHICAL SOFT COMPUTING; INDUSTRIAL PROCESSS; INTEGRATED APPROACH; INTELLIGENT MODELING; OPERATIONAL CONDITIONS; PROCESS VARIABLES;

INDUSTRIAL PLANTS;

EID: 33846785818     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIRA.2003.1222224     Document Type: Conference Paper

References (16)

1. R. Axelrod. Structure of Decision: the Cognitive Maps of Political Elites. Princeton University Press, New Jersey, 1976.
2. J. Craiger, D. Goodman, R. J. Weiss, and A. B. Butler. Modeling Organizational Behavior with Fuzzy Cognitive Maps. Int. J. of Computational Intelligence and Organizations, I, pp. 120-123, 1996.
3. K. Goto, and T. Yamaguchi. Fuzzy Associative Memory Application to a Plant Modeling. Proc. of the International Conference on Artificial Neural Networks (ICANN-91), Espoo, Finland, pp. 1245-1248, 1991.
4. M. Hadjiski, N. Christova, and P.P. Groumpos. Design of Hybrid Models for Complex Systems. Proc. ofESIT'99, Crete, 1999.
5. J. Jang, C. Sun and E. Mizutani. NeuroFuzzy and Soft Computing. Prentice Hall Publishing, 1997.
6. C.-F. Juang, and C.-T. Lin. An On-Line Self-Constructing Neural Fuzzy Inference Network and Its Applications. IEEE Trans, on Fuzzy Systems, 6 (1), pp. 12-32, 1998.
7. B. Kosko. Fuzzy Cognitive Maps. Int. J. of Man-Machine Studies, 24, pp. 65-75, 1986.
8. B. Kosko. Neural Networks and Fuzzy Systems: A Dynamical System Approach. Englewood Cliffs, NJ: Prentice-Hall, USA, 1992.
9. C. T. Lin, and G. Lee. Neural Fuzzy Systems: A Neuro-Fuzzy Synergism to Intelligent Systems, Prentice-Hall, Upper Saddle River N. J 1996.
10. R. Medsker. Hybrid Intelligent Systems. Kluwer Academic Publishers, 1995.
11. G. Saridis. Analytic formulation of the principle of Increasing Precision with Decreasing Intelligence for Intelligent Machines. Automatica, 25, pp. 461-467, 1989.
12. C. Stylios, and P. Groumpos. A soft computing approach for modeling the supervisor of manufacturing systems. Journal of Intelligent and Robotics Systems, 26 (3-4), pp. 389-403, 1999.
13. R. Taber. Knowledge Processing with Fuzzy Cognitive Maps. Expert Systems with Applications, 2, pp. 83-87, 1991.
14. T. Takagi, and M. Sugeno. Fuzzy Identification of Systems and Its Application to Modelling and Control. IEEE Trans, on Systems, Man and Cybernetics, 15(1), pp. 116-132, 1985.
15. G. Vachkov. Algorithms for Global and Local Learning of Fuzzy Models. Proceeding of the l4k Fuzzy Symposium SOFT'98, Gifu, Japan, WF3-3, pp. 321-324, 1998.
16. G. Vachtsevanos, and S. Kim. The role of the Human in Intelligent Control Practices. Proc. of 12th IEEE International Symposium on Intelligent Control, pp. 15-20, 1997.