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A machine learning-based model for the estimation of the temperature-dependent moduli of graphene oxide reinforced nanocomposites and its application in a thermally affected buckling analysis

Crossref DOI link: https://doi.org/10.1007/s00366-020-00945-9

Published Online: 2020-01-22

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Amani, Mohammad Amin

Ebrahimi, Farzad

Dabbagh, Ali

Rastgoo, Abbas

Nasiri, Mohammad Mahdi
License Information

Text and Data Mining valid from 2020-01-22

Version of Record valid from 2020-01-22
More Information

Article History

Received: 14 October 2019

Accepted: 7 January 2020

First Online: 22 January 2020

Compliance with ethical standards

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: The authors declare no conflict of interests during this study.

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