The application of deep neural networks for the prediction of California Bearing Ratio of road subgrade soil

The application of deep neural networks for the prediction of California Bearing Ratio of road subgrade soil

California Bearing Ratio (CBR) of the subgrade soil is one of the essential values for the design and construction of the asphalt pavement of highway projects. However, the estimation of the CBR value through laboratory tests is time-consuming and labor-intensive. Thus, this study focuses on providi...

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Bibliographic Details
Main Authors: Kareem Othman, Hassan Abdelwahab
Format: Article
Language:English
Published: Elsevier 2023-07-01
Series:Ain Shams Engineering Journal
Subjects:
Artificial neural networks
Atterberg limits
California bearing ratio
Index properties
Regression analysis
Subgrade
Online Access:http://www.sciencedirect.com/science/article/pii/S2090447922002994

Internet

http://www.sciencedirect.com/science/article/pii/S2090447922002994

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