Gradient Pre-shaped Fuzzy C-means Algorithm (GradPFCM) for transparent membership function generation

IEEE International Conference on Fuzzy Systems

Volumn , Issue , 2008, Pages 428-433

  Chen, Long ^a   Philip Chen, C L ^b  

^a UNIVERSITY OF TEXAS AT SAN ANTONIO   (United States)

^b University of Texas at San Antonio   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CIVIL PROJECTS; FUNCTION GENERATIONS; FUZZY C-MEANS; FUZZY C-MEANS ALGORITHMS; FUZZY MODELING; GRADIENT DESCENTS; LINGUISTIC TERMS; NEW ALGORITHMS; UNDERSTANDABILITY;

ALGORITHMS; CLUSTERING ALGORITHMS; FUZZY CLUSTERING; FUZZY LOGIC; FUZZY RULES; FUZZY SYSTEMS; LINGUISTICS; MICROCONTROLLERS; PROBABILITY DENSITY FUNCTION;

MEMBERSHIP FUNCTIONS;

EID: 55249122690     PISSN: 10987584     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.2008.4630403     Document Type: Conference Paper

References (24)

1. F. Hoppner, F. Klawonn, R. Kruse, and T. Runkler, Fuzzy Cluster Analysis. Chichester, Wiley, 1999.
2. H. Li, C. L. P. Chen, and H.-P. Huang, Fuzzy Neural Intelligent Systems: Mathematical Foundation and Application to Engineering, New York: CRC Press, 2000.
3. G. Castellano, A. M. Fanelli, and C. Menear, "A compact Gaussian representation of fuzzy information Granules," in Proceedings of Joint 1st International Conference On Soft Computing And Intelligent Systems And 3rd International Symposium On Advanced Intelligent Systems (SCIS&ISIS 2002), Tsukuba, 2002, pp. 21-25.
4. M.-S. Chen and S.-W. Wang, "Fuzzy clustering analysis for optimizing membership functions", Fuzzy Sets and Systems, vol. 103, 1999, pp. 239-254.
5. S. Medasani, J. Kim, and R. Krishnapuram, "An overview of membership function generation techniques for pattern recognition," Int. J. Approx. Reasoning, vol. 19, 1998, pp. 391-417.
6. L. A. Zadeh, "Fuzzy sets," Information and control, vol. 8, 1965, pp. 338-353.
7. W. Pedrycz and J. V. de Oliveira, "An R" reconstruction problem in linguistic interfaces", in Proc. of IFSA 2005 - The International Fuzzy Systems Association World Congress, Beijing, China, July, 2005.
8. W. Pedrycz and F. Gomide, An Introduction to Fuzzy Sets: Analysis and Design, Cambridge, MA, MIT Press, 1998.
9. F. Höppner and F. Klawonn, "A new approach to fuzzy partitioning," In Proc. of NAFIPS01, Vancouver, Canada, 2001, pp. 1419-1424.
10. L. Chen and C. L. P. Chen, "Pre-shaped Fuzzy C-means Algorithm (PFCM) for Transparent Membership Function Generation", In Proc. of IEEE International Conf. on SMC, Montreal, Canada, 2007, pp. 389-394
11. S.-K. Oh, W. Pedrycz and H.-S. Park, "Hybrid Identification in Fuzzy-Neural Networks," Fuzzy Sets and Systems, vol. 138, n. 2, 2003, pp. 399-426.
12. L. Chen, W. Pedrycz, and C. L. P. Chen, "Computational intelligence techniques for building transparent construction performance models," In Proc. of IEEE International Conf. on SMC, Taipei, Taiwan, 2006, pp.1166-1171.
13. T. W. Liao, A. K. Celmins, and R. J. Hammell, II, "A fuzzy c-means variant for the generation of fuzzy term sets," Fuzzy Sets and Systems, vol.135, n.2,2003, pp. 241-257.
14. R. Krishnapuram, "Generation of membership functions via possibilistic clustering," in Proc of 3rd IEEE Conf. on. Fuzzy System, 1994, vol. 3, pp. 902-908.
15. W. Pedrycz, "Logic-driven fuzzy modeling with fuzzy multiplexers," Engineering Applications of Artificial Intelligence, vol. 17, n. 4, pp 383-391
16. K.M. Lee, K.M. Lee, J.H. Lee, and H. Lee-Kwang, "A fuzzy decision tree induction method for fuzzy data," in Proceedings of IEEE International Fuzzy Systems Conference, 1999, vol. 1, pp. 16-21.
17. W. Pedrycz, "Logic-oriented fuzzy neural networks," Int. J. Hybrid Intell. Syst., vol. 1 n.1, 2004, pp. 3-11
18. M. Dissanayake, L. Chen, W. Pedrycz, A. Fayek, A. Russell, "Fuzzy logic modeling of causal relationships: reasoning about construction performance," in Proc. of 2004 NAFIPs International Conference, Alberta, Canada, 2004, vol. 2, pp. 605-610.
19. G. Castellano, A. M. Fanelli, C. Menear, "Design of transparent Mamdani fuzzy inference systems," in Proc of HIS 2003, pp. 468-477.
20. M. Pertselakis, D. S. Frossyniotis, and A. Stafylopatis, "An adaptable Gaussian neuro-fuzzy classifier," in Proc. of ICANN, 2003, pp. 925-932.
21. M. Setnes, R. Babuska, and H. B. Verbruggen, "Transparent fuzzy modeling: Data exploration and fuzzy sets aggregation," International Journal ofHuman Computer Studies, vol. 49, n.2, 1998, pp. 159-179.
22. A. Riid and E. Rüstern, "Transparent fuzzy systems and modeling with transparencyprotection," in Proc. IFACSymp. on Artificial Intelligence in Real Time Control, Budapest, Hungary, 2000, pp. 229-234.
23. G. Castellano, A. M. Fanelli, and C. Menear, "Fuzzy information granules: a compact, transparent and efficient representation," Journal of Advances Computational Intelligence and Intelligent Informatics, vol. 7, n.2, 2003, pp. 160-168
24. S. K. Halgamuge and M. Glesner, "Fast Transparent Neuro-Fuzzy Classifiers", in Proceedings of the 15th IASTED International Conference - Modelling, Identification and Control, Innsbruck, Austria, 1996, pp.407-410.