Using Neural Networks with data Quantization for time Series Analysis in LHC Superconducting Magnets Cover

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Using Neural Networks with data Quantization for time Series Analysis in LHC Superconducting Magnets

International Journal of Applied Mathematics and Computer Science

Volume 29 (2019): Issue 3 (September 2019)

By: Maciej Wielgosz and Andrzej Skoczeń

Open Access

|Sep 2019

Authors

Maciej Wielgosz

wielgosz@agh.edu.pl

Faculty of Computer Science, Electronics and Telecommunications, AGH University of Science and Technology, Cracow, Poland

Andrzej Skoczeń

skoczen@agh.edu.pl

Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Cracow, Poland

DOI: https://doi.org/10.2478/amcs-2019-0037 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X

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Language: English

Page range: 503 - 515

Submitted on: Oct 11, 2018

Accepted on: Apr 23, 2019

Published on: Sep 28, 2019

Published by: University of Zielona Góra

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

Large Hadron Collider,

LSTM architecture,

signal modelling

Related subjects:

Applied mathematics

© 2019 Maciej Wielgosz, Andrzej Skoczeń, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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