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Volumn 2, Issue 2, 2004, Pages 126-131

A hybrid neural architecture for fuzzy rules extraction;Uma arquitetura neural híbrida para extração de regras nebulosas

Author keywords

[No Author keywords available]

Indexed keywords

ANFIS MODEL; DATA ANALYSIS; FUNCTION PARAMETERS; INPUT-OUTPUT; NEURAL ARCHITECTURES; NEURO-FUZZY; OUTPUT FUNCTIONS; QUADRATIC ERRORS; RULES EXTRACTION; SECOND LAYER; SYNAPTIC WEIGHT; T - NORM; TAKAGI-SUGENO; TRAINING PROCESS;

EID: 57849149697     PISSN: 15480992     EISSN: None     Source Type: Journal    
DOI: 10.1109/TLA.2004.1468631     Document Type: Conference Paper
Times cited : (7)

References (27)
  • 1
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    • ANFIS: Adaptative-Network-Based Fuzzy Inference System
    • May/Jun
    • Jang, J.S.Roger, "ANFIS: Adaptative-Network-Based Fuzzy Inference System", IEEE Trans. on System, Man and Cybern 23 (3) pp.665-685 (May/Jun, 1993).
    • (1993) IEEE Trans. on System, Man and Cybern , vol.23 , Issue.3 , pp. 665-685
    • Jang, J.S.R.1
  • 9
    • 0027851250 scopus 로고
    • Function Approximator Using Fuzzy Rules Extracted Directly from Numerical Data
    • Shigeo Abe and Ming-Shong Lan: Function Approximator Using Fuzzy Rules Extracted Directly from Numerical Data. Proc. of the IEEE Int. Joint Conf. on Neural Networks Vol. 2, pp1887-1892. 1993.
    • (1993) Proc. of the IEEE Int. Joint Conf. on Neural Networks , vol.2 , pp. 1887-1892
    • Abe, S.1    Lan, M.-S.2
  • 12
    • 0002019319 scopus 로고    scopus 로고
    • Genetic Algorithms for Learning the Rule Base of Fuzzy Logic Controller
    • T.C. Chin and X.M. Qi: Genetic Algorithms for Learning the Rule Base of Fuzzy Logic Controller. Fuzzy Sets and Systems, Vol. 97, n 1, pp 1-7, 1998.
    • (1998) Fuzzy Sets and Systems , vol.97 , Issue.1 , pp. 1-7
    • Chin, T.C.1    Qi, X.M.2
  • 13
    • 0032155391 scopus 로고    scopus 로고
    • Autogeneration of Fuzzy Rules and Membership Functions for Fuzzy Modelling Using Rough Set Theory
    • Y. Cho and K. Lee and J. Yoo and M. Park: Autogeneration of Fuzzy Rules and Membership Functions for Fuzzy Modelling Using Rough Set Theory. IEE Proc.: Control Theory and Applications, Vol. 145, n 5, pp 437-442, 1998.
    • (1998) IEE Proc.: Control Theory and Applications , vol.145 , Issue.5 , pp. 437-442
    • Cho, Y.1    Lee, K.2    Yoo, J.3    Park, M.4
  • 17
    • 0027316584 scopus 로고
    • Gradient Descent Method for Optimizing Various Fuzzy Rule Bases
    • François Guély and Patrick Siarry: Gradient Descent Method for Optimizing Various Fuzzy Rule Bases. Proc. 2nd IEEE Int. Conf. on Fuzzy Systems, pp 1241-1246, 1993.
    • (1993) Proc. 2nd IEEE Int. Conf. on Fuzzy Systems , pp. 1241-1246
    • Guély, F.1    Siarry, P.2
  • 19
    • 0030289773 scopus 로고    scopus 로고
    • Induction of Fuzzy Rules and Membership Functions from Training Examples
    • Tzung-Pei Hong and Chai-Ying Lee: Induction of Fuzzy Rules and Membership Functions from Training Examples. Fuzzy Sets and Systems, Vol 84, pp 33-47, 1996.
    • (1996) Fuzzy Sets and Systems , vol.84 , pp. 33-47
    • Hong, T.-P.1    Lee, C.-Y.2
  • 26
    • 0027647258 scopus 로고
    • Similarity, Interpolation, and Fuzzy Rule Construction
    • Thomas Sudkamp: Similarity, Interpolation, and Fuzzy Rule Construction. Fuzzy Sets and Systems, Vol. 58, n 1, pp 73-86, 1993.
    • (1993) Fuzzy Sets and Systems , vol.58 , Issue.1 , pp. 73-86
    • Sudkamp, T.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.