130 citations
- Sakarya Uygulamalı Bilimler Üniversitesi6 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR4 papers
- Gebze Technical UniversityTR4 papers
- A. Alikhanyan National LaboratoryAM3 papers
- Arizona State UniversityUS3 papers
- Carnegie Mellon UniversityUS3 papers
- Catholic University of AmericaUS3 papers
- CEA Paris-SaclayFR3 papers
- CEA Paris-Saclay - Etablissement de SaclayFR3 papers
- Christopher Newport UniversityUS3 papers
- Florida International UniversityUS3 papers
- Florida State UniversityUS3 papers
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cs.AI2025
Predicting California Bearing Ratio with Ensemble and Neural Network Models: A Case Study from Turkiye
Abdullah Hulusi Kökçam, Uğur Dağdeviren, Talas Fikret Kurnaz +2
The California Bearing Ratio (CBR) is a key geotechnical indicator used to assess the load-bearing capacity of subgrade soils, especially in transportation infrastructure and found…
cs.AI2025★ 1 cited
Soil Compaction Parameters Prediction Based on Automated Machine Learning Approach
Caner Erden, Alparslan Serhat Demir, Abdullah Hulusi Kokcam +2
Soil compaction is critical in construction engineering to ensure the stability of structures like road embankments and earth dams. Traditional methods for determining optimum mois…