| Introducing stacking machine learning approaches for the prediction of rock deformation M Koopialipoor, PG Asteris, AS Mohammed, DE Alexakis, A Mamou, ... Transportation Geotechnics 34, 100756, 2022 | 106 | 2022 |
| Soft computing based closed form equations correlating L and N-type Schmidt hammer rebound numbers of rocks PG Asteris, A Mamou, M Hajihassani, M Hasanipanah, M Koopialipoor, ... Transportation Geotechnics 29, 100588, 2021 | 95 | 2021 |
| Predicting the unconfined compressive strength of granite using only two non-destructive test indexes DJ Armaghani, A Mamou, C Maraveas, PC Roussis, VG Siorikis, ... Geomech. Eng 25 (4), 317-330, 2021 | 89 | 2021 |
| Closed-form equation for estimating unconfined compressive strength of granite from three non-destructive tests using soft computing models AD Skentou, A Bardhan, A Mamou, ME Lemonis, G Kumar, P Samui, ... Rock Mechanics and Rock Engineering 56 (1), 487-514, 2023 | 87 | 2023 |
| Genetic prediction of ICU hospitalization and mortality in COVID‐19 patients using artificial neural networks PG Asteris, E Gavriilaki, T Touloumenidou, EE Koravou, M Koutra, ... Journal of cellular and molecular medicine 26 (5), 1445-1455, 2022 | 71 | 2022 |
| The effects of drainage on the behaviour of railway track foundation materials during cyclic loading A Mamou, W Powrie, JA Priest, C Clayton Géotechnique 67 (10), 845-854, 2017 | 64 | 2017 |
| Rock-burst occurrence prediction based on optimized Naïve Bayes models B Ke, M Khandelwal, PG Asteris, AD Skentou, A Mamou, DJ Armaghani Ieee Access 9, 91347-91360, 2021 | 47 | 2021 |
| Correlating the unconfined compressive strength of rock with the compressional wave velocity effective porosity and schmidt hammer rebound number using artificial neural networks TT Le, AD Skentou, A Mamou, PG Asteris Rock Mechanics and Rock Engineering 55 (11), 6805-6840, 2022 | 36 | 2022 |
| The effectiveness of ensemble-neural network techniques to predict peak uplift resistance of buried pipes in reinforced sand J Zeng, PG Asteris, AP Mamou, AS Mohammed, EA Golias, DJ Armaghani, ... Applied Sciences 11 (3), 908, 2021 | 34 | 2021 |
| On random subspace optimization-based hybrid computing models predicting the california bearing ratio of soils DK Trong, BT Pham, FE Jalal, M Iqbal, PC Roussis, A Mamou, ... Materials 14 (21), 6516, 2021 | 33 | 2021 |
| Predicting clay compressibility using a novel Manta ray foraging optimization-based extreme learning machine model PG Asteris, A Mamou, M Ferentinou, TT Tran, J Zhou Transportation Geotechnics 37, 100861, 2022 | 31 | 2022 |
| Bagging and multilayer perceptron hybrid intelligence models predicting the swelling potential of soil DD Nguyen, PC Roussis, BT Pham, M Ferentinou, A Mamou, DQ Vu, ... Transportation Geotechnics 36, 100797, 2022 | 26 | 2022 |
| Behaviour of saturated railway track foundation materials during undrained cyclic loading A Mamou, J Priest, CRI Clayton, W Powrie Canadian Geotechnical Journal 55 (5), 689-697, 2018 | 24 | 2018 |
| The effect of mass eccentricity on the torsional response of building structures GK Georgoussis, A Mamou Structural Engineering and Mechanics 67 (6), 671-682, 2018 | 19 | 2018 |
| Effects of principal stress rotation and drainage on the resilient stiffness of railway foundations A Mamou University of Southampton, 2013 | 13 | 2013 |
| Soft computing based closed form equations correlating L and N-type Schmidt hammer rebound numbers of rocks. Transp Geotech 2021 PG Asteris, A Mamou, M Hajihassani, M Hasanipanah, M Koopialipoor, ... | 11 | 2021 |
| The role of clay content on the response of railway track foundations during free-to-drain cyclic changes in principal stress rotation A Mamou, C Clayton, W Powrie, J Priest Transportation Geotechnics 20, 100246, 2019 | 11 | 2019 |
| Investigation of subgrade stabilization life-extending benefits in flexible pavements using a non-linear mechanistic-empirical analysis AR Ghanizadeh, M Salehi, A Mamou, EI Koutras, F Jalali, PG Asteris Infrastructures 9 (2), 33, 2024 | 7 | 2024 |
| Mass eccentricity effects on the torsional response of inelastic buildings GK Georgoussis, A Mamou Vibroengineerig Procedia 23, 66-71, 2019 | 6 | 2019 |
| Deep neural networks for the estimation of granite materials’ compressive strength using non-destructive indices DJ Armaghani, AD Skentou, M Izadpanah, M Karoglou, M Khandelwal, ... Applications of Artificial Intelligence in Mining and Geotechnical …, 2024 | 3 | 2024 |
Panagiotis G. AsterisProfessor, School of Pedagogical and Technological Education, Athens, GreecePreverjeni e-poštni naslov na aspete.gr
