Faruk Ergen 
- : Improved forecasting of the compressive strength of ultra‐high‐performance concrete (UHPC) via the CatBoost model optimized with different algorithms. Dans: Structural Concrete.
- (2024): Machine and deep learning-based prediction of flexural moment capacity of ultra-high performance concrete beams with/out steel fiber. Dans: Asian Journal of Civil Engineering, v. 25, n. 6 (24 juin 2024).
- (2024): Development of ontological algorithms for exact QTO of reinforced concrete construction items. Dans: Structures, v. 60 (février 2024).
- (2024): Investigation of optimized machine learning models with PSO for forecasting the shear capacity of steel fiber-reinforced SCC beams with/out stirrups. Dans: Journal of Building Engineering, v. 83 (avril 2024).
- (2024): Data-driven moment-carrying capacity prediction of hybrid beams consisting of UHPC-NSC using machine learning-based models. Dans: Structures, v. 59 (janvier 2024).
Structurae coopère avec
