Comprehensive mechanical property classification of vapor-grown carbon nanofiber/vinyl ester nanocomposites using support vector machines-Reference-Cited by-同舟云学术

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Comprehensive mechanical property classification of vapor-grown carbon nanofiber/vinyl ester nanocomposites using support vector machines

Published:2015-03 Issue: Volume:99 Page:316-325
ISSN:0927-0256
Container-title:Computational Materials Science
language:en
Short-container-title:Computational Materials Science

Author:

Abuomar O.,Nouranian S.,King R.,Ricks T.M.,Lacy T.E.

Publisher

Elsevier BV

Subject

Computational Mathematics,General Physics and Astronomy,Mechanics of Materials,General Materials Science,General Chemistry,General Computer Science

Reference47 articles.

1. Pattern Recognition;Theodoridis,2008

2. Applying support vector machines to imbalanced datasets;Akbani,2004

3. Materials informatics

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2. Predicting the AC Conductivity of Nanocomposite Films using the Bagging Model;Polymer Science, Series A;2022-12

3. Advances in Computational Intelligence of Polymer Composite Materials: Machine Learning Assisted Modeling, Analysis and Design;Archives of Computational Methods in Engineering;2022-01-31

4. Predictions of the mechanical properties of unidirectional fibre composites by supervised machine learning;Scientific Reports;2019-09-27

5. Application of materials informatics to vapor-grown carbon nanofiber/vinyl ester nanocomposites through self-organizing maps and clustering techniques;Computational Materials Science;2019-02

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