Time-series prediction using adaptive neuro-fuzzy networks

International Journal of Systems Science

Volumn 35, Issue 5, 2004, Pages 273-286

  Lin, Cheng Jian ^a  

^a CHAOYANG UNIVERSITY OF TECHNOLOGY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE SYSTEMS; COMPUTER SIMULATION; FORECASTING; FORMAL LOGIC; FUZZY SETS; GENETIC ALGORITHMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; MEMBERSHIP FUNCTIONS; TIME SERIES ANALYSIS;

ADAPTIVE NEURO FUZZY NETWORKS; HYBRID LEARNING ALGORITHM; TIME SERIES PREDICTION;

NEURAL NETWORKS;

EID: 3142702099     PISSN: 00207721     EISSN: None     Source Type: Journal    
DOI: 10.1080/00207720410001714130     Document Type: Article

References (34)

1. Anderson, C. W., 1987, Strategy learning with multilayer connectionist representations. Proceedings of the Fourth International Workshop on Machine Learning, Irvine, CA, June 1987, pp. 103-114.
2. Berenji, H. R., and Khedkar, P., 1992, Learning and tuning fuzzy logic controllers through reinforcements. IEEE Transactions on Neural Networks, 3, 724-740.
3. Chen, S. M., and Hwang, J. R., 2000, Temperature prediction using fuzzy time series. IEEE Transactions on Systems, Man, and Cybernetics, 30, 263-275.
4. Goldberg, D. E., 1989, Genetic Algorithms in Search, Optimization and Machine Learning (Reading, MA: Addison-Wesley).
5. Homaifar, A., and McCormick, E., 1995, Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms. IEEE Transactions on Fuzzy Systems, 3, 129-139.
6. Hwang, J. R., Chen S. M., and Lee, C. H., 1998, Handling forecasting problems using fuzzy time series. Fuzzy Sets and Systems, 100, 217-228.
7. Ishibuchi, H., Nozaki, K., Yamamoto, N., and Tanaka, H., 1995, Selecting fuzzy if-then rules for classification problems using genetic algorithms. IEEE Transactions on Fuzzy Systems, 3, 260-270.
8. Jang, J. S., 1992, Self-learning fuzzy controllers based on temporal back propagation. IEEE Transactions on Neural Networks, 3, 723-741.
9. Jang, J. S., 1993, ANFIS: Adaptive-Network Based Fuzzy Inference System. IEEE Transactions on System, Man, and Cybernetics, 23, 665-685.
10. Karr, C., 1991a, Genetic algorithms for fuzzy controllers. AI Expert, February, 26-33.
11. Karr, C., 1991b, Applying genetics to fuzzy logic. AI Expert, March, 39-43.
12. Klassen, M. S., and Pao, Y. H., 1988, Characteristics of the functional-link net: a higher order delta rule net. IEEE Proceedings of the Conference on Neural Networks, San Diego, June.
13. Kosko, B., 1992, Neural Networks and Fuzzy Systems (Englewood Cliff, NJ: Prentice Hall).
14. Lee, C. C., 1990, Fuzzy logic in control systems: fuzzy logic controller - Part I and Part II. IEEE Transactions on Systems, Man, and Cybernetics, 20, 404-435.
15. Lee, M. A., and Takagi, H., 1993, Integrating design stages of fuzzy systems using genetic algorithms. Proceerdings of the IEEE International Conference Fuzzy Systems, 612-617.
16. Lin, C. T., and Jou, C. P., 2000, GA-based fuzzy reinforcement learning for control of a magnetic bearing system. IEEE Transaction on Systems, Man, and Cybernetics, 30, 276-289.
17. Lin, C. T., and Lee, C. S. G., 1991, Neural-network-based fuzzy logic control and decision system. IEEE Transactions on Computers, C-40, 1320-1336.
18. Lin, C. J., and Lin, C. T., 1997, An ART-based fuzzy adaptive learning control network. IEEE Transactions on Fuzzy Systems, 5, 477-496.
19. Montana, D., and Davis, L., 1989, Training feedforward neural networks using genetic algorithms. Proceedings of the International Joint Conference on Artificial Intelligence, pp. 762-767.
20. Nauck, D., and Kruse, R., 1993, A fuzzy neural network learning fuzzy control rules and membership functions by fuzzy error back-propagation. Proceedings of the IEEE International Conference on Neural Networks, 1022-1027.
21. Nomura, H., Hayashi, I., and Wakami, N., 1992, A self-tuning method of fuzzy reasoning by genetic algorithm. Proceedings of the IEEE International Conference on Fuzzy Systems, 236-245.
22. Ogata, K., 1987, Discrete-Time Control Systems (Englewood Cliffs, NJ: Pretice-Hall).
23. Setnes, M., and Roubos, H., 2000, GA-fuzzy modeling and classification: complexity and performance. IEEE Transactions on Fuzzy Systems, 8, 509-522.
24. Song, Q., and Chissom, B. S., 1993, Fuzzy time series and its model. Fuzzy Sets and Systems, 54, 269-277.
25. Sugeno, M., 1985, An introduction survey of fuzzy control. Information Science, 36, 59-83.
26. Sugeno, M., and Yasukawa, T., 1993, A fuzzy-logic-based approach to qualitative modeling. IEEE Transactions on Fuzzy Systems, 1, 7-31.
27. Tagaki, T., and Hayashi, I., 1991, NN-driven fuzzy reasoning. International Journal of Approximate Reasoning, 5, 191-212.
28. Takagi, T., and Sugeno, M., 1985, Fuzzy identification of systems and its applications to modeling and control. IEEE Transactions Systems, Man, Cybernetics, 15, 116-132.
29. Thrift, P., 1991, Fuzzy logic synthesis with genetic algorithms. Proceedings of the International Conference on Genetic Algorithms, San Diego, July 1991, pp. 509-513.
30. Wang, L. X., and Mendel, J. M., 1992, Generating fuzzy rules by learning from examples. IEEE Transactions on Systems, Man, and Cybernetics, 22, 1414-1427.
31. Wang, L., and Yen, J., 1999, Extracting fuzzy rules for system modeling using a hybrid of genetic algorithm and Kalman filter. Fuzzy Sets and Systems, 101, 353-362.
32. Werbos, P. J., 1992, Neural control and fuzzy logic: connections and designs, International Journal of Approximate Reasoning, 6, 185-219.
33. Whitley, D., Starkweather, T., and Bogart, C., 1990, Genetic algorithm and neural networks: optimizing connections and connectivity. Parallel Computing, 14, 347-361.
34. Yager, R. R., 1992, Implementing fuzzy logic controller using a neural network. Fuzzy Sets and Systems, 48, 53-64.