Adaptive fuzzy inference neural network

Pattern Recognition

Volumn 37, Issue 10, 2004, Pages 2049-2057

  Iyatomi, Hitoshi ^a   Hagiwara, Masafumi ^a  

^a KEIO UNIVERSITY   (Japan)

Author keywords

Fuzzy inference; Fuzzy modeling and rule extraction; Machine learning; Neural network

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; ALGORITHMS; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; NEURAL NETWORKS; PROBLEM SOLVING;

FUZZY INFERENCE; FUZZY MODELING AND RULE EXTRACTION; FUZZY SYSTEMS; SELF-ORGANIZATION LEARNING;

INFERENCE ENGINES;

EID: 4544268143     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2004.04.003     Document Type: Article

References (20)

1. T. Takagi, M. Sugeno, Structure identification of systems and its application to modelling and control, IEEE Trans. Systems Man Cybern. 15 (1985) 116-132.
2. C.-T. Lin, C. Lee, Neural-network-based fuzzy logic control and decision systems, IEEE Trans. Comput. (special issue on Artificial Neural Networks) 40 (1991) 1320-1336.
3. A. Amano, T. Arisuka, On the use of neural networks and fuzzy logic in speech recognition, in: Proceedings of the International Joint Conference on Neural Networks, 1989, pp. 301-305.
4. Y. Lin, G.A. Cunningham, A new approach to fuzzy-neural system modeling, IEEE Trans. Fuzzy Systems 3 (1995) 190-197.
5. C. Wong, C.C. Chen, A hybrid clustering and gradient descent approach for fuzzy modeling, IEEE Trans. Systems, Man Cybern. 29 (1999) 686-693.
6. D.A. Linkens, M.-Y. Chen, Input selection and partition validation for fuzzy modeling using neural network, Fuzzy Sets Systems 107 (1999) 299-308.
7. M.-Y. Chen, D.A. Linkens, A systematic neuro-fuzzy modeling framework with application to material property prediction, IEEE Trans. Systems, Man Cybern. 31(5) (2001) 781-790.
8. T. Kohonen, The self-organizing map, Proc. IEEE 78(9) (1990) 1464-1480.
9. Jyh-Shing, R. Jang, ANFIS: adaptive-network-based fuzzy inference system, IEEE Trans. Systems, Man Cybern. 23(3) (1993) 665-685.
10. Li-Xin Wang, Training of fuzzy logic systems using nearest neighborhood clustering, in: Proceedings of the Second IEEE International Conference on Fuzzy Systems, Vol. 1, 1993, pp. 93-100.
11. T. Nishina, M. Hagiwara, Fuzzy inference neural network, Neurocomputing 14 (1997) 223-239.
12. H. Iyatomi, M. Hagiwara, Knowledge extraction from scenery images and the recognition using fuzzy inference neural networks, Trans. IEICE (D-II) J82-D-II(4) (1999) 685-693 (in Japanese).
13. H. Iyatomi, M. Hagiwara, Scenery image recognition and interpretation using fuzzy inference neural networks, Pattern Recognition 35(8) (2002) 1793-1806.
14. S.L. Chiu, Selecting input variables for fuzzy models, J. Intell. Fuzzy Systems 4 (1996) 243-256.
15. C.-F. Juang, C.-T. Lin, An on-line self-constructing neural fuzzy inference network and its applications, IEEE Trans. Fuzzy Systems 6 (1998) 12-32.
16. M. Sugeno, T. Yasukawa, A fuzzy-logic-based approach to qualitative modeling, IEEE Trans. Fuzzy Systems 1 (1993) 7-31.
17. N.R. Pal, J.C. Bedzek, On cluster validity for c-means model, IEEE Trans. Fuzzy Systems 3 (1995) 370-379.
18. UCI Machine Laming Repository, http://www.ics.uci.edu/mlearn/.
19. M. Fanty, R. Cole, Advances in Neural Information Processing Systems, Vol. 3, San Mateo, CA, 1991
20. B. Zupan, M. Bohanec, I. Bratko, J. Demsar, Machine learning by function decomposition, ICML-97, Nashville, TN, 1997.