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Volumn 12, Issue 2-3, 2005, Pages 183-194

Artificial Neural Network as a numerical form of effective constitutive law for composites with parametrized and hierarchical microstructure

Author keywords

Hierarchical composite; Homogenisation; Neural network

Indexed keywords

APPROXIMATION THEORY; COMPOSITE MATERIALS; FRACTALS; FUNCTION EVALUATION; GEOMETRY; HIERARCHICAL SYSTEMS; NUMERICAL METHODS; PARAMETER ESTIMATION;

EID: 29744446462     PISSN: 1232308X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (12)

References (15)
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  • 2
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  • 6
    • 29744468344 scopus 로고    scopus 로고
    • Use of artificial neural network to define a non-linear effective constitutive law for a composite
    • XIII Polish Conference on Computer Methods in Mechanics, Poznań
    • M. Lefik. Use of artificial neural network to define a non-linear effective constitutive law for a composite. Proceedings of XIII Polish Conference on Computer Methods in Mechanics, XIII Polish Conference on Computer Methods in Mechanics, 723-732, Poznań 1997.
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    • Lefik, M.1
  • 7
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    • One-dimensional model of cable-in-conduit superconductors under cyclic loading using artificial neural networks
    • M. Lefik, B.A. Schrefler. One-dimensional model of cable-in-conduit superconductors under cyclic loading using artificial neural networks. Fusion Engineering and Design, Elsevier Science, 60 (2): 105-117, 2002.
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    • Lefik, M.1    Schrefler, B.A.2
  • 8
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    • Artificial Neural Network for parameter identifications for an elasto-plastic model of super-conducting cable under cyclic loading
    • M. Lefik, B.A. Schrefler. Artificial Neural Network for parameter identifications for an elasto-plastic model of super-conducting cable under cyclic loading. Computers & Structures, 80 (22): 1699-1713, 2002.
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    • Lefik, M.1    Schrefler, B.A.2
  • 9
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    • Artificial neural network as an incremental non-linear constitutive model for a finite element code
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.