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Volumn 104, Issue 2, 1999, Pages 199-208

Fuzzy modeling with hybrid systems

Author keywords

Fuzzy clustering; Fuzzy modeling; Generating and tuning; Genetic algorithms; Hybrid systems

Indexed keywords


EID: 0001165190     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-0114(97)00206-6     Document Type: Article
Times cited : (47)

References (21)
  • 9
    • 0029297062 scopus 로고
    • Structure optimization of fuzzy neural network by genetic algorithms
    • [9] H. Ishigami, T. Fukuda, T. Shibta, F. Arai, Structure optimization of fuzzy neural network by genetic algorithms, Fuzzy Sets and Systems 71 (1995) 257-264.
    • (1995) Fuzzy Sets and Systems , vol.71 , pp. 257-264
    • Ishigami, H.1    Fukuda, T.2    Shibta, T.3    Arai, F.4
  • 10
    • 0028729506 scopus 로고
    • MECA: Maximun entropy clustering algorithm
    • [10] N.B. Karayiannis, MECA: Maximun entropy clustering algorithm, Proc. IEEE, 1994, pp. 630-1648.
    • (1994) Proc. IEEE , pp. 630-1648
    • Karayiannis, N.B.1
  • 12
    • 0041121700 scopus 로고
    • Method of fuzzy inference suitable for fuzzy control
    • [12] M. Mizumoto, Method of fuzzy inference suitable for fuzzy control, J. Soc. Instr. Control Eng. 58 (1989) 959-963.
    • (1989) J. Soc. Instr. Control Eng. , vol.58 , pp. 959-963
    • Mizumoto, M.1
  • 13
    • 0021455631 scopus 로고
    • An identification algorithm in fuzzy relational systems
    • [13] W. Pedrycz, An identification algorithm in fuzzy relational systems, Fuzzy Sets and Systems 13 (1984) 153-167.
    • (1984) Fuzzy Sets and Systems , vol.13 , pp. 153-167
    • Pedrycz, W.1
  • 14
    • 0027186778 scopus 로고
    • Fuzzy system designing through fuzzy clustering and optimal predefuzzification
    • [14] S.K. Sin, R.J.P. de Figueiredo, Fuzzy system designing through fuzzy clustering and optimal predefuzzification, Proc. IEEE, 1993, pp. 190-195.
    • (1993) Proc. IEEE , pp. 190-195
    • Sin, S.K.1    De Figueiredo, R.J.P.2
  • 15
    • 0027544110 scopus 로고
    • A fuzzy-logic-based approach to qualitative modeling
    • [15] M. Sugeno, T. Yasukawa, A fuzzy-logic-based approach to qualitative modeling, IEEE Trans. Fuzzy Systems 1 (1993) 7-31.
    • (1993) IEEE Trans. Fuzzy Systems , vol.1 , pp. 7-31
    • Sugeno, M.1    Yasukawa, T.2
  • 16
    • 0026943536 scopus 로고
    • Generating fuzzy rules by learning from examples
    • [16] L. Wang, J.M. Mendel, Generating fuzzy rules by learning from examples, IEEE Trans. Systems Man Cybernet. 22 (1992) 1414-1427.
    • (1992) IEEE Trans. Systems Man Cybernet. , vol.22 , pp. 1414-1427
    • Wang, L.1    Mendel, J.M.2
  • 19
    • 0024738274 scopus 로고
    • Stabilization of an inverted pendulum by a high-speed fuzzy logic controller hardware system
    • [19] T. Yamakawa, Stabilization of an inverted pendulum by a high-speed fuzzy logic controller hardware system, Fuzzy Sets and Systems 32 (1989) 161-180.
    • (1989) Fuzzy Sets and Systems , vol.32 , pp. 161-180
    • Yamakawa, T.1
  • 20
    • 0004683439 scopus 로고
    • Construction of fuzzy models through clustering techniques
    • [20] Y. Yoshinari, W. Pedrycz, K. Hirota, Construction of fuzzy models through clustering techniques, Fuzzy Sets and Systems 54 (1993) 157-165.
    • (1993) Fuzzy Sets and Systems , vol.54 , pp. 157-165
    • Yoshinari, Y.1    Pedrycz, W.2    Hirota, K.3
  • 21
    • 0000938740 scopus 로고    scopus 로고
    • A learning process for fuzzy control rules using genetic algorithms
    • [21] F. Herrera, M. Lozano, J.L. Verdegay, A learning process for fuzzy control rules using genetic algorithms, Fuzzy Sets and Systems 100 (1998) 143-158.
    • (1998) Fuzzy Sets and Systems , vol.100 , pp. 143-158
    • Herrera, F.1    Lozano, M.2    Verdegay, J.L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.