Taoufik Najeh
- (2024): Predicting the properties of concrete incorporating graphene nano platelets by experimental and machine learning approaches. In: Case Studies in Construction Materials, v. 20 (July 2024).
- (2024): Forecasting maximum formwork pressure for self-compacting concrete using ARX-Laguerre machine learning model. In: Developments in the Built Environment, v. 18 (April 2024).
- (2024): Comparing the efficacy of GEP and MEP algorithms in predicting concrete strength incorporating waste eggshell and waste glass powder. In: Developments in the Built Environment, v. 17 (March 2024).
- (2024): Data-driven approaches for strength prediction of alkali-activated composites. In: Case Studies in Construction Materials, v. 20 (July 2024).
- (2024): Predictive modeling for compressive strength of 3D printed fiber-reinforced concrete using machine learning algorithms. In: Case Studies in Construction Materials, v. 20 (July 2024).
- (2024): Predictive modeling for depth of wear of concrete modified with fly ash: A comparative analysis of genetic programming-based algorithms. In: Case Studies in Construction Materials, v. 20 (July 2024).
- (2024): Application of metaheuristic optimization algorithms in predicting the compressive strength of 3D-printed fiber-reinforced concrete. In: Developments in the Built Environment, v. 17 (March 2024).
Structurae cooperates with
