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Support vector machines for characterising whipple shield performance

journal contribution

posted on 2023-10-23, 23:41 authored by Shannon RyanShannon Ryan, S Kandanaarachchi, K Smith-Miles

Support vector machines for characterising whipple shield performance

History

Journal

Procedia Engineering

Volume

103

Pagination

522-529

Location

Boulder, CO

Publisher DOI

https://doi.org/10.1016/j.proeng.2015.04.068

Link to full text

https://doi.org/10.1016/j.proeng.2015.04.068

ISSN

1877-7058

eISSN

1877-7058

Language

English

Author URL

http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000380535200067&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a045e4b2bb1f2b747c68c720ec8913b7

Publication classification

C1 Refereed article in a scholarly journal

Editor/Contributor(s)

Schonberg WP

Publisher

ELSEVIER SCIENCE BV

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Categories

No categories selected

Keywords

Science & Technology Technology Engineering, Multidisciplinary Engineering Hypervelocity impact Whipple shield Artificial Neural Network Support Vector Machine Machine Learning

Licence

All Rights Reserved

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