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Correlation between Cone Penetration Test parameters, soil type, and soil liquidity index using long short-term memory neural network Cover

Correlation between Cone Penetration Test parameters, soil type, and soil liquidity index using long short-term memory neural network

Studia Geotechnica et Mechanica
Volume 45 (2023): Issue s1 (December 2023)
By: Mateusz Jocz and  Marek Lefik  
Open Access
|Nov 2023
DOI: https://doi.org/10.2478/sgem-2023-0023 | Journal eISSN: 2083-831X | Journal ISSN: 0137-6365
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Language: English
Page range: 405 - 415
Submitted on: Mar 3, 2023
Accepted on: Oct 4, 2023
Published on: Nov 13, 2023
Published by: Wroclaw University of Science and Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
geotechnical parameters,
Cone Penetration Test (CPTU),
liquidity index,
Long Short-Term Memory (LSTM) neural network
Related subjects:
Geosciences,
Geosciences, other,
Materials sciences,
Composites,
Porous materials,
Physics,
Mechanics and fluid dynamics

© 2023 Mateusz Jocz, Marek Lefik, published by Wroclaw University of Science and Technology
This work is licensed under the Creative Commons Attribution 4.0 License.

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