- Predicting the properties of concrete incorporating graphene nano platelets by experimental and machine learning approaches. Dans: Case Studies in Construction Materials, v. 20 (juillet 2024). (2024):
- Forecasting the strength of nanocomposite concrete containing carbon nanotubes by interpretable machine learning approaches with graphical user interface. Dans: Structures, v. 59 (janvier 2024). (2024):
- Predictive modelling of sustainable lightweight foamed concrete using machine learning novel approach. Dans: Journal of Building Engineering, v. 56 (septembre 2022). (2022):
- Predicting the compressive strength of concrete with fly ash admixture using machine learning algorithms. Dans: Construction and Building Materials, v. 308 (novembre 2021). (2021):
- Geopolymer concrete as sustainable material: A state of the art review. Dans: Construction and Building Materials, v. 306 (novembre 2021). (2021):
- (2021): Compressive Strength Prediction via Gene Expression Programming (GEP) and Artificial Neural Network (ANN) for Concrete Containing RCA. Dans: Buildings, v. 11, n. 8 (27 juillet 2021).
- Micro-cracking pattern recognition of hybrid CNTs/GNPs cement pastes under three-point bending loading using acoustic emission technique. Dans: Journal of Building Engineering, v. 42 (octobre 2021). (2021):
- (2021): Compressive Strength of Fly-Ash-Based Geopolymer Concrete by Gene Expression Programming and Random Forest. Dans: Advances in Civil Engineering, v. 2021 (janvier 2021).
- Exploring mechanical performance of hybrid MWCNT and GNMP reinforced cementitious composites. Dans: Construction and Building Materials, v. 267 (janvier 2021). (2021):
- (2020): Applications of Gene Expression Programming for Estimating Compressive Strength of High-Strength Concrete. Dans: Advances in Civil Engineering, v. 2020 (janvier 2020).
- Sugarcane bagasse ash-based engineered geopolymer mortar incorporating propylene fibers. Dans: Journal of Building Engineering, v. 33 (janvier 2021). (2021):