Implementation of deep neural networks and statistical methods to predict the resilient modulus of soils
The Resilient Modulus (Mr) is perhaps the most relevant and widely used parameter to characterise the soil behaviour under repetitive loading for pavement applications. Accordingly, it is a crucial parameter controlling the mechanistic-empirical pavement design. Nonetheless, determining the Mr by la...
- Autores:
-
Polo Mendoza, Rodrigo
Duque, Jose
Mašín, David
Turbay, Emilio
Acosta, Carlos
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2023
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/14276
- Acceso en línea:
- https://hdl.handle.net/11323/14276
https://repositorio.cuc.edu.co/
- Palabra clave:
- Deep neural networks
Resilient modulus
US soils
Statistical methods
- Rights
- closedAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)