메뉴 건너뛰기




Volumn 50, Issue 1-2, 2006, Pages 90-104

Design of hierarchical fuzzy model for classification problem using GAs

Author keywords

Classification problem; Genetic algorithms; Hierarchical fuzzy model; Knowledge acquisition

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER SIMULATION; DATABASE SYSTEMS; FUZZY CONTROL; GENETIC ALGORITHMS; KNOWLEDGE ACQUISITION; PROBLEM SOLVING;

EID: 33744510962     PISSN: 03608352     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cie.2005.06.007     Document Type: Article
Times cited : (9)

References (30)
  • 1
    • 0347705521 scopus 로고    scopus 로고
    • Partial correlation of fuzzy sets
    • Chiang D.A., and Lin N.P. Partial correlation of fuzzy sets. Fuzzy Sets Systems 110 (2000) 209-215
    • (2000) Fuzzy Sets Systems , vol.110 , pp. 209-215
    • Chiang, D.A.1    Lin, N.P.2
  • 2
    • 33744511976 scopus 로고    scopus 로고
    • Forina, M., & Wine Recognition Database (1991). Available via anonymous ftp from ics.uci.edu indirectory/pub/machine-learning-databases.
  • 3
    • 0031360860 scopus 로고    scopus 로고
    • Holve, R. (1997). Rule generation for hierarchical fuzzy systems. In Proceedings of NAFIPS '97 (pp. 444-449).
  • 5
    • 0034510120 scopus 로고    scopus 로고
    • Ishibuchi, H., Aguirre, H. E. & Tanaka, K. S. (2000). Multi-objective optimization with improved genetic algorithm. In Proceedings of the IEEE international conference on SMC (pp. 3852-3857).
  • 6
    • 0000919523 scopus 로고    scopus 로고
    • Single-objective and two-objective genetic algorithms for selecting linguistic rules for pattern classification problems
    • Ishibuchi H., Murata T., and Turksen B. Single-objective and two-objective genetic algorithms for selecting linguistic rules for pattern classification problems. Fuzzy Sets Systems 89 (1997) 135-150
    • (1997) Fuzzy Sets Systems , vol.89 , pp. 135-150
    • Ishibuchi, H.1    Murata, T.2    Turksen, B.3
  • 7
    • 0032597810 scopus 로고    scopus 로고
    • Performance evaluation of fuzzy classifier systems for multidimensional pattern classification problems
    • Ishibuchi H., and Nakashima T. Performance evaluation of fuzzy classifier systems for multidimensional pattern classification problems. IEEE Transactions on Systems, Man, Cybern-Part B: Cybernetics 29 (1999) 601-617
    • (1999) IEEE Transactions on Systems, Man, Cybern-Part B: Cybernetics , vol.29 , pp. 601-617
    • Ishibuchi, H.1    Nakashima, T.2
  • 9
    • 0030576819 scopus 로고    scopus 로고
    • Learning fuzzy rules and approximate reasoning in fuzzy neural networks and hybrid system
    • Kasabov N.K. Learning fuzzy rules and approximate reasoning in fuzzy neural networks and hybrid system. Fuzzy Sets Systems 82 (1996) 135-149
    • (1996) Fuzzy Sets Systems , vol.82 , pp. 135-149
    • Kasabov, N.K.1
  • 10
    • 0033309691 scopus 로고    scopus 로고
    • GA-based fuzzy PI/PD controller for automotive active suspension system
    • Kuo Y.P., and Li T.-H.S. GA-based fuzzy PI/PD controller for automotive active suspension system. IEEE Transactions on Industrial Electronics (1999) 1051-1056
    • (1999) IEEE Transactions on Industrial Electronics , pp. 1051-1056
    • Kuo, Y.P.1    Li, T.-H.S.2
  • 12
    • 0033900560 scopus 로고    scopus 로고
    • Design of a GA-based fuzzy PID controller for non-minimum phase systems
    • Li T.-H.S., and Shieh M.-Y. Design of a GA-based fuzzy PID controller for non-minimum phase systems. Fuzzy Sets Systems 11 (2000) 183-197
    • (2000) Fuzzy Sets Systems , vol.11 , pp. 183-197
    • Li, T.-H.S.1    Shieh, M.-Y.2
  • 13
    • 0031630903 scopus 로고    scopus 로고
    • Linkens, D. A. & Chen, M. Y. (1998). Hierarchical fuzzy clustering based on self-organizing networks. In Proceedings of the IEEE international conference on Fuzzy systems (pp. 1406-1410).
  • 14
    • 0032594811 scopus 로고    scopus 로고
    • Applying genetic algorithms to search for the best hierarchical clustering of a dataset
    • Lozano J.A., and Larranaga P. Applying genetic algorithms to search for the best hierarchical clustering of a dataset. Pattern Recognition Letters 20 (1999) 911-918
    • (1999) Pattern Recognition Letters , vol.20 , pp. 911-918
    • Lozano, J.A.1    Larranaga, P.2
  • 15
    • 0037209903 scopus 로고    scopus 로고
    • Multi-item fuzzy EOQ models using genetic algorithm
    • Mondal S., and Maiti M. Multi-item fuzzy EOQ models using genetic algorithm. Computers and Industrial Engineering 44 (2003) 105-117
    • (2003) Computers and Industrial Engineering , vol.44 , pp. 105-117
    • Mondal, S.1    Maiti, M.2
  • 16
    • 0001703957 scopus 로고    scopus 로고
    • A neuro-fuzzy method to learn fuzzy classification rules from data
    • Nauck D., and Kruse R. A neuro-fuzzy method to learn fuzzy classification rules from data. Fuzzy Sets Systems 89 (1997) 277-288
    • (1997) Fuzzy Sets Systems , vol.89 , pp. 277-288
    • Nauck, D.1    Kruse, R.2
  • 18
    • 0032638857 scopus 로고    scopus 로고
    • Padmanabhan, M. & Bahl, L. R. (1999). Partitioning the feature space of a classifier with linear hyperplanes. In Proceedings of the IEEE transactions on speech and audio (pp. 282-288).
  • 19
    • 0033906947 scopus 로고    scopus 로고
    • Fuzzy rule based classification with feature selector and modified threshold accepting
    • Ravi V., and Zimmermann J. Fuzzy rule based classification with feature selector and modified threshold accepting. European Journal of Operational Research 123 (2000) 16-28
    • (2000) European Journal of Operational Research , vol.123 , pp. 16-28
    • Ravi, V.1    Zimmermann, J.2
  • 20
    • 0344213749 scopus 로고    scopus 로고
    • Neuro-genetic approach to multidimensional fuzzy reasoning for pattern classification
    • Ray K.S., and Ghoshal J. Neuro-genetic approach to multidimensional fuzzy reasoning for pattern classification. Fuzzy Sets Systems 112 (2000) 449-483
    • (2000) Fuzzy Sets Systems , vol.112 , pp. 449-483
    • Ray, K.S.1    Ghoshal, J.2
  • 21
    • 0030127431 scopus 로고    scopus 로고
    • Further examination of fuzzy linear regression
    • Redden D.T. Further examination of fuzzy linear regression. Fuzzy Sets Systems 79 (1996) 203-211
    • (1996) Fuzzy Sets Systems , vol.79 , pp. 203-211
    • Redden, D.T.1
  • 22
    • 0033704206 scopus 로고    scopus 로고
    • Roubos, H. & Setnes, M. (2000). Compact fuzzy models through complexity reduction and evolutionary optimization. In Process IEEE international conference on fuzzy systems (pp. 762-767).
  • 23
    • 0001875235 scopus 로고
    • Evaluation of fuzzy linear regression model
    • Savic D.A., and Pedrycz W. Evaluation of fuzzy linear regression model. Fuzzy Sets Systems 39 (1991) 51-63
    • (1991) Fuzzy Sets Systems , vol.39 , pp. 51-63
    • Savic, D.A.1    Pedrycz, W.2
  • 24
    • 0029296855 scopus 로고
    • Self-tuning fuzzy modeling with adaptive membership function, rule, and hierarchical structure based on genetic algorithm
    • Shimojima K., Fukuda T., and Hasegawa Y. Self-tuning fuzzy modeling with adaptive membership function, rule, and hierarchical structure based on genetic algorithm. Fuzzy Sets Systems 71 (1995) 295-309
    • (1995) Fuzzy Sets Systems , vol.71 , pp. 295-309
    • Shimojima, K.1    Fukuda, T.2    Hasegawa, Y.3
  • 25
    • 0034249310 scopus 로고    scopus 로고
    • Using genetic algorithms to work out index configuration for the class-hierarchy indexing in object databases
    • Song H.J., and Kim H.J. Using genetic algorithms to work out index configuration for the class-hierarchy indexing in object databases. Information and Software Technology 42 (2000) 731-741
    • (2000) Information and Software Technology , vol.42 , pp. 731-741
    • Song, H.J.1    Kim, H.J.2
  • 26
    • 38249035267 scopus 로고
    • Fuzzy data analysis by possibility linear models
    • Tanaka H. Fuzzy data analysis by possibility linear models. Fuzzy Sets Systems 24 (1987) 363-375
    • (1987) Fuzzy Sets Systems , vol.24 , pp. 363-375
    • Tanaka, H.1
  • 27
    • 0001325256 scopus 로고    scopus 로고
    • Insight of a fuzzy regression model
    • Wang H.F., and Tsaur R.C. Insight of a fuzzy regression model. Fuzzy Sets Systems 112 (2000) 355-369
    • (2000) Fuzzy Sets Systems , vol.112 , pp. 355-369
    • Wang, H.F.1    Tsaur, R.C.2
  • 28
    • 0033078158 scopus 로고    scopus 로고
    • A new method for constructing membership functions and fuzzy rules from training examples
    • Wu T.P., and Chen S.M. A new method for constructing membership functions and fuzzy rules from training examples. IEEE Transactions on Systems, Man, Cybern-Part B: Cybernetics 29 (1999) 334-347
    • (1999) IEEE Transactions on Systems, Man, Cybern-Part B: Cybernetics , vol.29 , pp. 334-347
    • Wu, T.P.1    Chen, S.M.2
  • 29
    • 0036712901 scopus 로고    scopus 로고
    • A scalable, incremental learning algorithm for classification problems
    • Ye N., and Li X. A scalable, incremental learning algorithm for classification problems. Computers and Industrial Engineering 43 (2002) 677-692
    • (2002) Computers and Industrial Engineering , vol.43 , pp. 677-692
    • Ye, N.1    Li, X.2
  • 30
    • 0030283584 scopus 로고    scopus 로고
    • A genetic algorithm for generating fuzzy classification rules
    • Yuan Y., and Zhuang H. A genetic algorithm for generating fuzzy classification rules. Fuzzy Sets Systems 84 (1996) 1-19
    • (1996) Fuzzy Sets Systems , vol.84 , pp. 1-19
    • Yuan, Y.1    Zhuang, H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.