Hybrid robust approach for TSK fuzzy modeling with outliers

Expert Systems with Applications

Volumn 36, Issue 5, 2009, Pages 8925-8931

  Chuang, Chen Chia ^a   Jeng, Jin Tsong ^b   Tao, Chin Wang ^a  

^a NATIONAL ILAN UNIVERSITY   (Taiwan)

^b NATIONAL FORMOSA UNIVERSITY   (Taiwan)

Author keywords

Hybrid robust approach; Outliers; Robust clustering algorithm; Robust learning algorithm; TSK fuzzy model

Indexed keywords

DISTRIBUTION FUNCTIONS; EDUCATION; FUZZY CONTROL; LEARNING ALGORITHMS; LEARNING SYSTEMS; MATHEMATICAL MODELS; NEURAL NETWORKS; REGRESSION ANALYSIS; TUNING;

HYBRID ROBUST APPROACH; OUTLIERS; ROBUST CLUSTERING ALGORITHM; ROBUST LEARNING ALGORITHM; TSK FUZZY MODEL;

CLUSTERING ALGORITHMS;

EID: 60849085425     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2008.11.053     Document Type: Article

References (35)

1. Angelov P.P., and Filev D.P. An approach to on-line identification of TS fuzzy models. IEEE Transactions on Systems Man Cybernetics: Part B 34 (2004) 484-498
2. Babuska R. Fuzzy modeling for control (1998), Kluwer Academic Publishers, Boston
3. Backer E., and Jain A.K. A clustering performance measure based on the fuzzy set decomposition. IEEE Transactions on Pattern Analysis and Machine Intelligence 13 (1981) 66-74
4. Bezdek J.C. Pattern recognition with fuzzy objective function algorithm (1981), Plenum
5. Chang P.C., and Liu C.H. A TSK type fuzzy rule based system for stock price prediction. Expert Systems with Applications 34 (2008) 135-144
6. Chen D.S., and Jain R.C. A robust back-propagation learning algorithm for function approximation. IEEE Transactions on Neural Networks 5 (1994) 467-479
7. Chuang C.C., Su S.F., and Chen S.S. Robust TSK fuzzy modeling for function approximation with outliers. IEEE Transactions on Fuzzy Systems 9 (2001) 810-821
8. Chuang C.C., Su S.F., and Hsiao C.C. The annealing robust backpropagation (ARBP) learning algorithm. IEEE Transactions on Neural Networks 11 (2000) 1067-1078
9. Chuang C.C., Su S.F., Jeng J.T., and Hsiao C.C. Robust support vector regression networks for function approximation with outliers. IEEE Transactions on Neural Networks 13 (2002) 1322-1330
10. Dave R.N., and Krishnapurum R. Robust clustering methods: A unified view. IEEE Transactions on Fuzzy Systems 5 (1997) 270-293
11. David V., and Sanchez A. Robustization of learning method for RBF networks. Neurocomputing 9 (1995) 85-94
12. Delgado M., Gómez Skarmeta A.F., and Vila A. On the use of hierarchical clustering in fuzzy modeling. International Journal of Approximate Reasoning 14 (1996) 237-259
13. Dickerson J.A., and Kosko B. Fuzzy function approximation with ellipsoidal rules. IEEE Transactions on Systems, Man and Cybernetics 26 (1996) 542-560
14. Euntai K., Minkee P., Seunghwan J., and Mignon P. A new approach to fuzzy modeling. IEEE Transactions on Fuzzy Systems 5 (1997) 328-337
15. Evans M., Hastings N., and Peacock B. Statistical distributions (1993), Wiley
16. Frigui H., and Krishnapuram R. A robust algorithm for automatic extraction of an unknown number of clusters from noise data. Pattern Recognition Letters 17 (1996) 1223-1232
17. Frigui H., and Krishnapuram R. A robust competitive clustering algorithm with applications in computer vision. IEEE Transactions on Pattern Analysis and Machine Intelligence 21 (1999) 450-465
18. Gu H., and Wang H. Fuzzy prediction of chaotic time series based on singular value decomposition. Applied Mathematics and Computation 185 (2007) 1171-1185
19. Hampel F.R., Ronchetti E.M., Rousseeuw P.J., and Stahel W.A. Robust statistics, the approach based on influence functions (1986), Wiley
20. Hathaway R.J., and Bezdek J.C. Switching regression models and fuzzy clustering. IEEE Transactions on Fuzzy Systems 1 (1993) 195-204
21. Hawkins D.M. Identification of outliers (1980), Chapman and Hall
22. Jain A.K., and Dubes R.C. Algorithms for clustering data (1988), Prentice Hall, Englewood Cliffs, NJ
23. Jeng J.T. Hybrid approach of selecting hyper-parameters of support vector machine for regression. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics 36 (2006) 699-709
24. Kim K., Kyung K.M., Park C.W., Kim E., and Park M. Robust TSK fuzzy modeling approach using noise clustering concept for function approximation. Lecture Notes in Computer Science (Computational & Information Science) 3314 2004 (2004) 538-543
25. Kim K., Whang E.J., Park C.W., Kim E., and Park M. A TSK fuzzy inference algorithm for on line identification. Lecture Notes in Computer Science (Computational & Information Science) 3613 2005 (2005) 179-188
26. Klawonn F., and Kruse R. Constructing a fuzzy controller from data. Fuzzy Sets and Systems 85 (1997) 177-193
27. Kwak K.C., and Kim D.K. TSK-based linguistic fuzzy model with uncertain model output. IEICE Transactions on Information and Systems E89 (2006) 2919-2923
28. Leski J.M. Epsilon-insensitive fuzzy C-regression models: Introduction to epsilon-insensitive fuzzy modeling. IEEE Transactions on Systems, Man and Cybernetics, Part B 34 (2004) 4-15
29. Leski J.M. TSK fuzzy modeling based on ε - Insensitive learning. IEEE Transactions on Fuzzy Systems 13 (2005) 181-193
30. Rousseeuw P.J., and Leroy M.A. Robust regression and outlier detection (1987), Wiley, New York
31. Simpson P.K. Fuzzy min-max neural networks - Part 2: Clustering. IEEE Transactions on Fuzzy Systems 1 (1993) 32-45
32. Sugeno M., and Yasukawa T. A fuzzy-logic-based approach to qualitative modeling. IEEE Transactions on Fuzzy Systems 1 (1993) 7-31
33. Takagi T., and Sugeno M. Fuzzy identification of systems and its applications to modeling and control. IEEE Transactions on Systems, Man and Cybernetics 15 (1985) 223-231
34. van den Bergh, W. M., & van den Berg, J. (2000). Competitive exception learning using fuzzy frequency distributions. ERIM Report Series Research in Management .
35. Wang W.Y., Lee T.T., Liu C.L., and Wang C.H. Function approximation using fuzzy neural networks with robust learning algorithm. IEEE Transactions on Systems, Man and Cybernetics, Part B 27 (1997) 740-747