Machine learning techniques and multi-scale models to evaluate the impact of silicon dioxide (SiO2) and calcium oxide (CaO) in fly ash on the compressive strength of green concreteDilshad Kakasor Ismael Jaf, Panagiotis G. Asteris, Payam Ismael Abdulrahman et al.|Construction and Building Materials|2023Cited by 307
Prediction of concrete materials compressive strength using surrogate modelsWael Emad, Panagiotis G. Asteris, Ahmed Salih Mohammed et al.|Structures|2022Cited by 219
Introducing stacking machine learning approaches for the prediction of rock deformationMohammadreza Koopialipoor, Danial Jahed Armaghani, Panagiotis G. Asteris et al.|Transportation Geotechnics|2022Cited by 153
Revealing the nature of metakaolin-based concrete materials using artificial intelligence techniquesPanagiotis G. Asteris, Kypros Pilakoutas, Paulo B. Lourénço et al.|Construction and Building Materials|2022Cited by 138
Analysis and prediction of the effect of Nanosilica on the compressive strength of concrete with different mix proportions and specimen sizes using various numerical approachesReyam Ali, Panagiotis G. Asteris, Maryam Muayad et al.|Structural Concrete|2022Cited by 123