메뉴 건너뛰기




Volumn 138, Issue 2, 2003, Pages 399-426

Hybrid identification in fuzzy-neural networks

Author keywords

Clustering; Fuzzy neural networks; Genetic algorithm; Hybrid identification; Improved complex method

Indexed keywords

APPROXIMATION THEORY; BACKPROPAGATION; FUNCTIONS; GENETIC ALGORITHMS; LEARNING ALGORITHMS; NEURAL NETWORKS; NONLINEAR SYSTEMS;

EID: 0043092359     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-0114(02)00441-4     Document Type: Article
Times cited : (84)

References (20)
  • 4
    • 0028268852 scopus 로고
    • On the principles of fuzzy neural net-works
    • Gupta M.M., Rao D.H. On the principles of fuzzy neural net-works. Fuzzy Sets and Systems. 61:1994;1-18.
    • (1994) Fuzzy Sets and Systems , vol.61 , pp. 1-18
    • Gupta, M.M.1    Rao, D.H.2
  • 5
    • 0008089137 scopus 로고
    • Are genetic algorithms function optimizers?
    • R. Manner, B. Manderick (Eds.), North-Holland, Amsterdam
    • K.A. De Jong, Are genetic algorithms function optimizers? in: R. Manner, B. Manderick (Eds.), Parallel Problem Solving from Nature 2, North-Holland, Amsterdam, 1992.
    • (1992) Parallel Problem Solving from Nature , vol.2
    • De Jong, K.A.1
  • 6
    • 0032164985 scopus 로고    scopus 로고
    • A simply identified Sugeno-type fuzzy model via double clustering
    • Kim E., Lee H., Park M., Park M. A simply identified Sugeno-type fuzzy model via double clustering. Inform. Sci. 110:1998;25-39.
    • (1998) Inform. Sci. , vol.110 , pp. 25-39
    • Kim, E.1    Lee, H.2    Park, M.3    Park, M.4
  • 7
  • 9
    • 0009015317 scopus 로고    scopus 로고
    • Fuzzy identification by means of an auto-tuning algorithm and a weighted performance index
    • in Korean
    • Oh S.K. Fuzzy identification by means of an auto-tuning algorithm and a weighted performance index. J. Fuzzy Logic Intelligent Systems. 8(6):1998;106-108. (in Korean).
    • (1998) J. Fuzzy Logic Intelligent Systems , vol.8 , Issue.6 , pp. 106-108
    • Oh, S.K.1
  • 10
    • 0034300570 scopus 로고    scopus 로고
    • Identification of fuzzy systems by means of an auto-tuning algorithm and its application to nonlinear systems
    • Oh S.K., Pedrycz W. Identification of fuzzy systems by means of an auto-tuning algorithm and its application to nonlinear systems. Fuzzy Sets and Systems. 115(2):2000;205-230.
    • (2000) Fuzzy Sets and Systems , vol.115 , Issue.2 , pp. 205-230
    • Oh, S.K.1    Pedrycz, W.2
  • 11
    • 0000181608 scopus 로고    scopus 로고
    • The design of optimal fuzzy-neural networks structure by means of GA and an aggregate weighted performance index
    • in Korean
    • Oh S.K., Yoon K.C., Kim H.K. The design of optimal fuzzy-neural networks structure by means of GA and an aggregate weighted performance index. J. Control Automat. Systems Eng. 6(3):2000;273-283. (in Korean).
    • (2000) J. Control Automat. Systems Eng. , vol.6 , Issue.3 , pp. 273-283
    • Oh, S.K.1    Yoon, K.C.2    Kim, H.K.3
  • 12
    • 0035467258 scopus 로고    scopus 로고
    • Identification of fuzzy models with the aid of evolutionary data granulation
    • Park B.J., Pedrycz W., Oh S.K. Identification of fuzzy models with the aid of evolutionary data granulation. IEE Proc. - CTA. 148(05):2001;406-418.
    • (2001) IEE Proc. - CTA , vol.148 , Issue.5 , pp. 406-418
    • Park, B.J.1    Pedrycz, W.2    Oh, S.K.3
  • 13
    • 0021455631 scopus 로고
    • An identification algorithm in fuzzy relational system
    • Pedrycz W. An identification algorithm in fuzzy relational system. Fuzzy Sets and Systems. 13:1984;153-167.
    • (1984) Fuzzy Sets and Systems , vol.13 , pp. 153-167
    • Pedrycz, W.1
  • 14
    • 0042594105 scopus 로고
    • x emissions using polynomial neural network
    • Georgia Institute of Technology, Atlanta
    • x emissions using polynomial neural network, Technical Report, Georgia Institute of Technology, Atlanta, 1995.
    • (1995) Technical Report
    • Vachtsevanos, G.1    Ramani, V.2    Hwang, T.W.3
  • 15
    • 0000257826 scopus 로고
    • A neo fuzzy neuron and its applications to system identification and prediction of the system behavior
    • Japan
    • T. Yamakawa, A neo fuzzy neuron and its applications to system identification and prediction of the system behavior, Proc. 2nd Internat. Conf. Fuzzy Logic and Neural Networks, pp. 477-483, Japan, 1992.
    • (1992) Proc. 2nd Internat. Conf. Fuzzy Logic and Neural Networks , pp. 477-483
    • Yamakawa, T.1
  • 16
    • 0000389470 scopus 로고
    • A new effective learning algorithm for a neo fuzzy neuron model
    • Korea
    • T. Yamakawa, A new effective learning algorithm for a neo fuzzy neuron model, 5th IFSA World Congr., pp. 1017-1020, Korea, 1993.
    • (1993) 5th IFSA World Congr. , pp. 1017-1020
    • Yamakawa, T.1
  • 17
    • 0042764607 scopus 로고    scopus 로고
    • Fuzzy-neural networks based on improved fuzzy input space and its optimization
    • October, Korea, in Korean
    • K.C. Yoon, B.J. Park, S.K. Oh, Fuzzy-neural networks based on improved fuzzy input space and its optimization, Proc. 14th KACC, Vol. B, October 1999, Korea, pp. B_314-B_317, (in Korean).
    • (1999) Proc. 14th KACC , vol.B
    • Yoon, K.C.1    Park, B.J.2    Oh, S.K.3
  • 19
    • 0015558134 scopus 로고
    • Outline of a new approach to the analysis of complex systems and decision processes
    • Zadeh L.A. Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans. System Man Cybernet. 3:1973;28-44.
    • (1973) IEEE Trans. System Man Cybernet. , vol.3 , pp. 28-44
    • Zadeh, L.A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.