Skip to main content
Have a personal or library account? Click to login
Suitability Determination of Machine Learning Techniques for the Operational Quality Assessment of Geophysical Survey Results Cover

Suitability Determination of Machine Learning Techniques for the Operational Quality Assessment of Geophysical Survey Results

Applied Computer Systems
Volume 25 (2020): Issue 2 (December 2020)
By:  and    
Open Access
|Dec 2020
Authors

Authors

Kirill Abramov

abramc@mail.ru

Branch Office “Geotehnocenter” of JSC Volcovgeology, Almaty, Kazakhstan

Janis Grundspenkis

Janis.Grundspenkis@rtu.lv

Riga Technical University, Riga, Latvia
DOI: https://doi.org/10.2478/acss-2020-0017 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683
Journal RSS Feed
Language: English
Page range: 153 - 162
Published on: Dec 28, 2020
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
Classification trees,
machine learning,
neural networks,
well logging
Related subjects:
Computer sciences,
Artificial intelligence,
Information technology,
Project management,
Software development

© 2020 Kirill Abramov, Janis Grundspenkis, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 25 (2020): Issue 2 (December 2020)
Previous article
Next article