Prediction of California bearing ratio and modified proctor parameters using deep neural networks and multiple linear regression: A case study of granular soils
Author:
Funder
Center for Geosphere Dynamics, Charles University
Grantová Agentura České Republiky
Publisher
Elsevier BV
Subject
Materials Science (miscellaneous)
Reference137 articles.
1. The effect of overconsolidation on monotonic and cyclic behaviours of frozen subgrade soil;Zhou;Transp. Geotech.,2022
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3. Implementation of deep neural networks and statistical methods to predict the resilient modulus of soils;Polo-Mendoza;Int. J. Pavement Eng.,2023
4. Chapter 7: advanced modelling approaches;Mašín,2018
5. Soil behavior and characterization: effect of improvement in CBR characteristics of soil subgrade on design of bituminous pavements;Mukherjee;Indian Geotech. J.,2021
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