Modeling and Prediction of Temporal Biogeomechanical Properties Using Novel Machine Learning Approach
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geology,Geotechnical Engineering and Engineering Geology,Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00603-023-03353-9.pdf
Reference95 articles.
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3. Al-Anazi AF, Gates ID (2015) On support vector regression to predict Poisson’s ratio and Young’s modulus of reservoir rock. In: Cranganu C, Luchian H, Breaban M (eds) Artificial intelligent approaches in petroleum geosciences. Springer, Cham. https://doi.org/10.1007/978-3-319-16531-8_5
4. Apostolopoulou M, Asteris PG, Armaghani DJ, Douvika MG, Lourenço PB, Cavaleri L, Bakolas A, Moropoulou A (2020) Mapping and holistic design of natural hydraulic lime mortars. Cem Concrete Res 136:106167. https://doi.org/10.1016/j.cemconres.2020.106167
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