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Volumn 2, Issue , 2010, Pages 33-36

Research on rules extraction from neural network based on linear insertion

Author keywords

Artificial neural network; Black box; Linear insertion; Symbolic rules

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BLACK BOXES; BLACK-BOX MODEL; LINEAR FUNCTIONS; LINEAR INSERTION; NONLINEAR MAPPINGS; NOVEL ALGORITHM; PIECE-WISE LINEAR FUNCTIONS; RULES EXTRACTION; SIMULATION EXPERIMENTS; SYMBOLIC RULES;

EID: 78049336968     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIE.2010.103     Document Type: Conference Paper
Times cited : (2)

References (13)
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    • Setiono, R.1
  • 2
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  • 3
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    • A Survey and Critique of Techniques for Extracting Rules from Trained Artificial Neural Networks
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    • Optimal Design of Radial Basis Function Neural Networks for Fuzzy-Rule Extraction in High Dimensional Data
    • Behloul, F., B.P.F. Lelieveldt, A. Boudraa, J.H.C. Reiber. Optimal Design of Radial Basis Function Neural Networks for Fuzzy-Rule Extraction in High Dimensional Data. Pattern Recognition, 2002, 35, 659-675.
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    • Behloul, F.1    Lelieveldt, B.P.F.2    Boudraa, A.3    Reiber, J.H.C.4
  • 9
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    • Symbolic presentation of neural networks
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    • R. Setiono, H. Liu. Symbolic presentation of neural networks. IEEE Computer, March 1996, pp. 71-77.
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    • Setiono, R.1    Liu, H.2
  • 10
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    • Castro J. L., Mantas C. J., and Benitez J. M. Interpretation of artificial neural networks by means of fuzzy rules. IEEE Transactions on Neural Networks, 2002, 13(1), 101-116.
    • (2002) IEEE Transactions on Neural Networks , vol.13 , Issue.1 , pp. 101-116
    • Castro, J.L.1    Mantas, C.J.2    Benitez, J.M.3
  • 11
    • 0033751611 scopus 로고    scopus 로고
    • Extracting M-of-N rules from trained neural networks
    • R. Setiono. Extracting M-of-N rules from trained neural networks. IEEE Transactions of Neural Networks, 2000, 11, 512-519.
    • (2000) IEEE Transactions of Neural Networks , vol.11 , pp. 512-519
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  • 12
    • 0036565303 scopus 로고    scopus 로고
    • Extraction of rules from artificial neural networks for nonlinear regression
    • Rudy Setiono, Wee Kheng Leow, Jacek M. Zurada, Extraction of rules from artificial neural networks for nonlinear regression. IEEE Transaction on Neural Networks, 2002, 13, 564-577
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  • 13
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    • An approach to generate rules from neural networks for regression problems
    • Rudy Setiono, James Y.L. Thong, An approach to generate rules from neural networks for regression problems. European Journal of Operational Research, 2004, 155(1), 239-250
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.