Identification of key variables using fuzzy average with fuzzy cluster distribution

IEEE Transactions on Fuzzy Systems

Volumn 15, Issue 4, 2007, Pages 673-685

  Hou, Yanfeng ^a   Zurada, Jacek M ^a   Karwowski, Waldemar ^a   Marras, William S ^b   Davis, Kermit ^c  

^a University of Louisville   (United States)

^b OHIO STATE UNIVERSITY   (United States)

^c UNIVERSITY OF CINCINNATI COLLEGE OF MEDICINE   (United States)

Author keywords

Fuzzy cluster; Variable identification

Indexed keywords

DATA PROCESSING; FUZZY CLUSTERING; FUZZY RULES;

FUZZY AVERAGE; FUZZY C-MEANS; VARIABLE IDENTIFICATION;

FUZZY SYSTEMS;

EID: 34548253479     PISSN: 10636706     EISSN: None     Source Type: Journal    
DOI: 10.1109/TFUZZ.2006.889897     Document Type: Article

References (21)

1. E. B. Bartlett, "Self determination of input variable importance by neural networks," Neural, Parallel Sci. Comp., vol. 2, no. 1, pp. 103-114, 1994.
2. B. Yuan and G. Klir, "Data-driven identification of key variables," in Intelligent Hybrid Systems - Fuzzy Logic, Neural Networks, and Genetic Algorithms, D. Ruan, Ed. Boston, MA: Kluwer Academic, 1997, pp. 161-186.
3. M. Sugeno and T. Yasukawa, "A fuzzy-logic-based approach to qualitative modeling," IEEE Trans. Fuzzy Syst., vol. 1, pp. 7-31, Feb. 1993.
4. S. L. Chiu, "Selecting input variables for fuzzy models," J. Intell. Fuzzy Syst., vol. 4, pp. 243-256, 1996.
5. Y. Lin and G. A. Cunningham, "A new approach to fuzzy-neural system modeling," IEEE Trans. Fuzzy Syst., vol. 3, pp. 190-198, May 1995.
6. Y. Lin, G. A. Cunningham, S. V. Coggeshall, and R. D. Jones, "Nonlinear system input structure identification: Two stage fuzzy curves and surfaces," IEEE Trans. Syst., Man, Cybern. A, vol. 28, pp. 678-684, Sep. 1998.
7. M. F. Azeem, M. Hanmandlu, and N. Ahmad, "Structure identification of generalized adaptive neuro-fuzzy inference systems," IEEE Trans. Fuzzy Syst., vol. 11, pp. 666-681, Oct. 2003.
8. E. C. Morabito and M. Versaci, "A fuzzy neural approach to localizing holes in conducting plates," IEEE Trans. Magn., vol. 37, no. 5, pp. 3534-3537, Sep. 2001.
9. S. E. Papadakis, J. B. Theocharis, J. Kiartzis, and A. G. Bakirtzis, "A novel approach to short-term load forecasting using fuzzy neural networks," IEEE Trans. Power Syst., vol. 13, pp. 480-492, May 1998.
10. A. H. Sung, "Ranking input importance in neural network modeling of engineering problems," in Proc. IEEE World Congr. Comp. Intell., May 1998, vol. 1, pp. 316-321.
11. B. Bouqata, A. Bensaid, R. Palliam, and A. F. Gomez Skarmeta, "Time series prediction using crisp and fuzzy neural networks: A comparative study," in Proc. IEEE/IAFE/INFORMS 2000 Conf. Comp. Intell. Financial Eng., Mar. 26-28, 2000, pp. 170-173.
12. M. F. Azeem, M. Hanmandlu, and N. Ahmad, "A new criteria for input variable identification of dynamical systems," in Proc. IEEE Region 10 Int. Conf. Global Connectivity Energy, Comput, Commun. Contr., Dec. 17-19, 1998, vol. 1, pp. 230-233.
13. S. Papadakis and J. Theocharis, "An efficient fuzzy neural modeling approach using the fuzzy curve concept," in Proc. 3rd IEEE Int. Conf. Electron., Circuits, Syst., Oct. 13-16, 1996, vol. 1, pp. 279-282.
14. E. S. Schrich, J. Ke, L. O. Hall, and D. B. Goldgof, "Fast accurate fuzzy clustering through data reduction," IEEE Trans. Fuzzy Syst. vol. 11, pp. 262-270, Apr. 2003.
15. G. E. P. Box and G. M. Jenkins, Time Series Analysis, Forecasting and Control, 2nd ed. San Francisco, CA: Holden Day, 1976.
16. A. E. Gaweda, J. M. Zurada, and R. Setiono, "Input selection in data-driven fuzzy modeling," in Proc. 10th IEEE Int. Conf. Fuzzy Syst., Dec. 2-5, 2001, vol. 3, pp. 1251-1254.
17. S. Auephanwiriyakul and J. M. Keller, "Analysis and efficient implementation of a linguistic fuzzy c-means," IEEE Trans. Fuzzy Syst., vol. 10, pp. 563-582, Oct. 2002.
18. Y. Hou, J. M. Zurada, and W. Karwowski, "Prediction of EMG signals of trunk muscles in manual lifting using a neural network model," in Proc. Int. Joint Conf. Neural Netw. (IJCNN 2004), Budapest, Hungary, Jul. 25-29, 2004, pp. 1935-1940.
19. J. Zurada, W. Karwowski, and W. S. Marras, "A neural network-based system for classification of industrial jobs with respect to the risk of low back disorders," Appl. Ergon., vol. 28, no. 1, pp. 49-58, 1997.
20. Y. Hou, J. M. Zurada, W. Karwowski, and W. S. Maras, "A fuzzy approach for key variables identification of EMG evaluation system," in Proc. Int. Joint Conf. Neural Netw. (IJCNN 2005 , Montreal, PQ, Canada, Jul. 31-Aug. 4 2005, pp. 2520-2525.
21. W. Lee, W. Karwowski, W. S. Marras, and D. Rodrick, "A neuro-fuzzy model for estimating electromyographical activity of trunk muscles due to manual lifting," Ergonomics, vol. 46, no. 1-3, pp. 285-309, Jan. 15, 2003.