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Machine learning methods for data driven theory in the physical sciences with applications to confinement regime identification in nuclear fusion

Publication Data

Title Machine learning methods for data driven theory in the physical sciences with applications to confinement regime identification in nuclear fusion
Contributors A. Murari, European Fusion Development Agreement, JET Project
Publisher JET-EFDA
Publication date 2009
Publication location Abingdon
Language English

Descriptive Notes

Publisher's no. : EFDA-JET-PR(09)04.

Topics

Nuclear fusion
Tokamaks
015539157

Catalogue Data

OBNB ID GBB059279
ISBN 10 n/a
ISBN 13 n/a
Type BibliographicResource, Book
Dewey Classification 621.484

ISBD

P1053 28 p.
P1042 Includes bibliographical references.

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Machine learning methods for data driven theory in the physical sciences with applications to confinement regime identification in nuclear fusion. Published by JET-EFDA in 2009. Publication and catalogue information, links to buy online and reader comments.