Transfer learning of deep material network for seamless structure–property predictions

Modern materials design requires reliable and consistent structure–property relationships. The paper addresses the need through transfer learning of deep material network (DMN). In the proposed learning strategy, we store the knowledge of a pre-trained network and reuse it to generate the initial st...

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Bibliographic Details
Published in:Computational Mechanics : Solids, Fluids, Structures, Fluid-Structure Interactions, Biomechanics, Micromechanics, Multiscale Mechanics, Materials, Constitutive Modeling, Nonlinear Mechanics, Aerodynamics, Vol. 64, No. 2 (2019), p. 451-465
Main Author: Liu, Zeliang
Other Involved Persons: Wu, T. ; Koishi, M.
Format: electronic Article
Language:English
ISSN:1432-0924
Physical Description:Online-Ressource
DOI:10.1007/s00466-019-01704-4
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