Odey Alshboul 
- (2024): A comparative study of LightGBM, XGBoost, and GEP models in shear strength management of SFRC-SBWS. In: Structures, v. 61 (March 2024).
- (2023): A comparative study of shear strength prediction models for SFRC deep beams without stirrups using Machine learning algorithms. In: Structures, v. 55 (September 2023).
- : Structural performance of buried reinforced concrete pipelines under deep embankment soil. In: Construction Innovation.
- (2023): Machine learning-based models for predicting the shear strength of synthetic fiber reinforced concrete beams without stirrups. In: Structures, v. 52 (June 2023).
- (2022): Evaluating the Impact of External Support on Green Building Construction Cost: A Hybrid Mathematical and Machine Learning Prediction Approach. In: Buildings, v. 12, n. 8 (31 July 2022).
- (2022): Machine Learning-Based Model for Predicting the Shear Strength of Slender Reinforced Concrete Beams without Stirrups. In: Buildings, v. 12, n. 8 (31 July 2022).
- (2022): Governmental Investment Impacts on the Construction Sector Considering the Liquidity Trap. In: Journal of Management in Engineering (ASCE), v. 38, n. 2 (March 2022).
- (2022): Risk Assessment Model for Optimal Gain–Pain Share Ratio in Target Cost Contract for Construction Projects. In: Journal of Construction Engineering and Management, v. 148, n. 2 (February 2022).
- (2021): Deep and machine learning approaches for forecasting the residual value of heavy construction equipment: a management decision support model. In: Engineering, Construction and Architectural Management, v. 29, n. 10 (October 2021).
- (2021): Machine learning models for predicting the residual value of heavy construction equipment: An evaluation of modified decision tree, LightGBM, and XGBoost regression. In: Automation in Construction, v. 129 (September 2021).
Structurae cooperates with
