A machine learning case study with limited data for prediction of carbon fiber mechanical properties

Golkarnarenji, Gelayol, Naebe, Minoo, Badii, Khashayar, Milani, Abbas S., Jazar, Reza N. and Khayyam, Hamid 2019, A machine learning case study with limited data for prediction of carbon fiber mechanical properties, Computers in industry, vol. 105, pp. 123-132, doi: 10.1016/j.compind.2018.11.004.

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Title A machine learning case study with limited data for prediction of carbon fiber mechanical properties
Author(s) Golkarnarenji, Gelayol
Naebe, MinooORCID iD for Naebe, Minoo orcid.org/0000-0002-0607-6327
Badii, Khashayar
Milani, Abbas S.
Jazar, Reza N.
Khayyam, Hamid
Journal name Computers in industry
Volume number 105
Start page 123
End page 132
Total pages 10
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2019-02
ISSN 0166-3615
Keyword(s) Science & Technology
Technology
Computer Science, Interdisciplinary Applications
Computer Science
Thermal stabilization process
Intelligent predictive models
Machine learning
Carbon fiber industry
Rendering parameters
Fiber mechanical properties
THERMAL-OXIDATIVE STABILIZATION
POLYACRYLONITRILE PRECURSOR
ACRYLIC FIBERS
PAN
OPTIMIZATION
MODEL
OXYGEN
CARBONIZATION
ALGORITHMS
MANAGEMENT
Language eng
DOI 10.1016/j.compind.2018.11.004
Field of Research 0803 Computer Software
0805 Distributed Computing
0910 Manufacturing Engineering
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2018, Elsevier B.V.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30118778

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