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Machine Learning Methods for Identifying Composition of Uranium Deposits in Kazakhstan Cover

Machine Learning Methods for Identifying Composition of Uranium Deposits in Kazakhstan

Applied Computer Systems
Volume 22 (2017): Issue 1 (December 2017)
By:  and    
Open Access
|Dec 2017
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DOI: https://doi.org/10.1515/acss-2017-0014 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683
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Language: English
Page range: 21 - 27
Published on: Dec 27, 2017
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
Data mining,
machine learning,
well logging surveys
Related subjects:
Computer sciences,
Artificial intelligence,
Information technology,
Project management,
Software development

© 2017 Yan Kuchin, Jānis Grundspeņķis, published by Riga Technical University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 22 (2017): Issue 1 (December 2017)
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