Modelling fuzzy production rules with fuzzy expert networks

Expert Systems with Applications

Volumn 13, Issue 3, 1997, Pages 169-178

  Tsang, E C C ^a   Yeung, D S ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; FUZZY SETS; KNOWLEDGE REPRESENTATION; LEARNING ALGORITHMS; MEMBERSHIP FUNCTIONS; NEURAL NETWORKS; PROBLEM SOLVING;

FUZZY EXPERT NETWORKS (FEN); FUZZY PRODUCTION RULES (FPR);

EXPERT SYSTEMS;

EID: 0031245728     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0957-4174(97)00029-8     Document Type: Article

References (36)

1. Adlassnig, K. P., & Kolarz, G. (1982). CAD/AG-2: Computer-assisted medical diagnosis using fuzzy subsets. In M. M. Gupta & E. Sanchez (Eds), Approximate reasoning in decision analysis (pp. 219-247). New York: North-Holland.
2. Buchanan, B. G., & Duda, R. O. (1982). Principles of rule-based expert systems. Lab for AI research, Fairchild Camera, Palo Alto, GA, Fairchild Tech. Rep. no. 626.
3. Buckley, J. J., & Hayshi, Y. (1994). Can fuzzy neural nets approximate continuous fuzzy functions?. Fuzzy Sets and Systems, 61, 43-51.
4. Chen, S. M. (1988). A new approach to handling fuzzy decision making problems. IEEE Transactions on Systems, Man and Cybernetics SMC, 18(6), 1012-1016.
5. Chen, S. M. (1994). A weighted fuzzy reasoning algorithm for medical diagnosis. Decision Support Systems, 11, 37-43.
6. Chen, S. M., Ke, J. S., & Chang, J. F. (1990). Knowledge representation using fuzzy Petri nets. IEEE Transaction on Knowledge and Data Engineering, 2(2), 311-319.
7. Fu, L. M., & Fu, L. C. (1990). Mapping rule-based systems into neural architecture. Knowledge-Based Systems, 3, 48-56.
8. Gallant, S. I. (1988). Connectionist expert systems. Communications of the ACM, 31, 152-169.
9. Garg, M. L., Ahson, S. I., & Gupta, P. V. (1991). A fuzzy Petri net for knowledge representation and reasoning. Information Processing Letters, 39, 165-171.
10. Hall, L., & Romaniuk, S. (1990). A hybrid connectionist symbolic learning system. In Proceedings of the AAAI-90, pp. 783-788.
11. Handelman, D. A., Land, S. H., & Gelfand, J. J. (1989). Integration of knowledge-based and neural network techniques for autonomous learning machines. Proceedings of the International Journal of Conferences on Neural Networks, 1, 683-688.
12. Hollatz, J. (1992). Supplementing neural network learning with rule-based knowledge. IJCNN, Bejing, China, 3-6 November, pp. 595-601.
13. Hruska, S. I., Kuncicky, D. C., & Lacher, R. C. (1991). Hybrid learning in expert networks. IJCNN, 91(II), 117-120.
14. Ishibuchi, H., Kwon, K., & Tanaka, H. (1995). A Learning algorithm of fuzzy neural networks with triangular fuzzy weights. Fuzzy Sets and Systems, 71, 277-293.
15. Kosko, B. (1992). Neural systems and fuzzy systems: a dynamical systems approach to machine intelligence. Englewood Cliffs: Prentice Hall.
16. Lacher, R. C., Hruska, S. I., & Kuncicky, C. (1992). Back-propagation learning in expert networks. IEEE Transactions on Neural Networks, 3(1), 62-72.
17. Lee, C. C. (1990), Fuzzy logic in control systems: fuzzy logic controller - part I. IEEE Transactions on System, Man, and Cybernetics, 20(2), 404-418.
18. Murphy, J. H. (1990). Probability-based neural networks. Proceedings of the IJCNN, 90(1), 451-454.
19. Ogawa, H., Fu, K. S., & Yao, J. T. P. (1985). An expert system for damage assessment of existing structures. In M. M. Gupta (Ed.), Approximate reasoning in expert systems (pp. 731-744). New York: North-Holland.
20. Sestito, S., & Dillon, T. (1993). Knowledge acquisition of conjunctive rules using multilayered neural networks. International Journal of Intelligent Systems, 8, 779-805.
21. Scharwartz, D. G., Klir, G. J., Lewis, H. W., & Ezawa, Y. (1994). Applications of fuzzy sets and approximate reasoning. Proceedings of the IEEE, 82(4), 482-498.
22. Sugeno, M. (1985). An introductory survey of fuzzy control. Information Sciences, 36, 59-83.
23. Tong, R. M. (1986). The representation of uncertainty in an expert system for information retrieval. Fuzzy logic in knowledge engineering. Germany: Verlag TUV Rheinland.
24. Touretzky, D., & Hinton, G. (1988). A distributed connectionist production system. Cognitive Science, 12, 423-466.
25. Towell, G. G., Shavlik, J. W., & Noordewier, M. O. (1990). Refinement of approximate domain theories by knowledge-based neural networks. Proceedings of the AAAI-90, 861-866.
26. Tsang, E. C. C., & Yeung, D. S. (1996). Learning capability of fuzzy expert networks. World Congress on Neural Networks, 15-18 Sept, San Diego, California, pp. 500-503.
27. Turksen, I. B., & Zhong, Z. (1988). An approximate analogical reasoning approach based on similarity measures. IEEE Transactions on Systems, Man and Cybernetics, 18(6), 1049-1056.
28. Whalen, T. S. (1986). Financial ratio analysis, fuzzy logic in knowledge engineering. Germany: Verlag TUV Rheinland.
29. Yager, R. (1984). Approximate reasoning as a basis for rule-based expert systems. IEEE Transactions on Systems Man, and Cybernetics, 14, 636-643.
30. Yager, R. (1994). Modeling and formulating fuzzy knowledge bases using neural networks. Neural Networks, 7(8), 1273-1283.
31. Widrow, B., Rumelhart, D. E., & Lehr, M. A. (1994). Neural networks: applications in industry, business and science. Communications of the ACM, 37(3), 93-105.
32. Yeung, D. S., & Tsang, E. C. C. (1992). Fuzzy production rules evaluation and fuzzy Petri nets. In Advances in computer cybernetics and information engineering. 1993 Collection of Selected Papers presented at the 6th International Conference on Systems Research, Informatics and Cybernetics, 17-23, August, Baden-Baden, Germany, pp. 137-142.
33. Yeung, D. S., & Tsang, E. C. C. (1994). Fuzzy knowledge representation and reasoning using Petri nets. Expert Systems with Applications, 7(2), 281-290.
34. Yeung, D. S., & Tsang, E. C. C. (1997). Weighted fuzzy production rules. Fuzzy Sets and Systems, 8, 299-313.
35. Yeung, D. S., & Tsang, E. C. C. (1997). A Comparative study on similarity-based fuzzy reasoning methods. IEEE Transactions on Systems Man, and Cybernetics, 27, 216-227.
36. Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning - I, II, III. Information Sciences, 8 and 9, 199-249, 301-357, 43-80.