Taoufik Najeh
- A scientometrics review of conventional and soft computing methods in the slope stability analysis. In: Frontiers in Built Environment, v. 10 (Februar 2024). (2024):
- Predicting the properties of concrete incorporating graphene nano platelets by experimental and machine learning approaches. In: Case Studies in Construction Materials, v. 20 (Juli 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 (März 2024). (2024):
- Data-driven approaches for strength prediction of alkali-activated composites. In: Case Studies in Construction Materials, v. 20 (Juli 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 (Juli 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 (Juli 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 (März 2024). (2024):