| Predicting the compressive strength of normal and High-Performance Concretes using ANN and ANFIS hybridized with Grey Wolf Optimizer EM Golafshani, A Behnood, M Arashpour Construction and Building Materials 232, 117266, 2020 | 357 | 2020 |
| Predicting the compressive strength of silica fume concrete using hybrid artificial neural network with multi-objective grey wolves A Behnood, EM Golafshani Journal of cleaner production 202, 54-64, 2018 | 299 | 2018 |
| Application of soft computing methods for predicting the elastic modulus of recycled aggregate concrete EM Golafshani, A Behnood Journal of cleaner production 176, 1163-1176, 2018 | 174 | 2018 |
| Estimation of the compressive strength of concretes containing ground granulated blast furnace slag using hybridized multi-objective ANN and salp swarm algorithm A Kandiri, EM Golafshani, A Behnood Construction and Building Materials 248, 118676, 2020 | 140 | 2020 |
| Machine learning study of the mechanical properties of concretes containing waste foundry sand A Behnood, EM Golafshani Construction and Building Materials 243, 118152, 2020 | 136 | 2020 |
| Estimating the optimal mix design of silica fume concrete using biogeography-based programming EM Golafshani, A Behnood Cement and Concrete Composites 96, 95-105, 2019 | 130 | 2019 |
| Prediction of bond strength of spliced steel bars in concrete using artificial neural network and fuzzy logic EM Golafshani, A Rahai, MH Sebt, H Akbarpour Construction and building materials 36, 411-418, 2012 | 129 | 2012 |
| Automatic regression methods for formulation of elastic modulus of recycled aggregate concrete EM Golafshani, A Behnood Applied Soft Computing 64, 377-400, 2018 | 99 | 2018 |
| Artificial neural network and genetic programming for predicting the bond strength of GFRP bars in concrete EM Golafshani, A Rahai, MH Sebt Materials and structures 48, 1581-1602, 2015 | 85 | 2015 |
| Bond behavior of steel and GFRP bars in self-compacting concrete EM Golafshani, A Rahai, MH Sebt Construction and Building Materials 61, 230-240, 2014 | 72 | 2014 |
| Determinants of the infection rate of the COVID-19 in the US using ANFIS and virus optimization algorithm (VOA) A Behnood, EM Golafshani, SM Hosseini Chaos, Solitons & Fractals 139, 110051, 2020 | 71 | 2020 |
| Predicting the compressive strength of self‐compacting concrete containing Class F fly ash using metaheuristic radial basis function neural network G Pazouki, EM Golafshani, A Behnood Structural Concrete 23 (2), 1191-1213, 2022 | 68 | 2022 |
| Prediction of self-compacting concrete elastic modulus using two symbolic regression techniques EM Golafshani, A Ashour Automation in Construction 64, 7-19, 2016 | 66 | 2016 |
| Evaluating the synergic effect of waste rubber powder and recycled concrete aggregate on mechanical properties and durability of concrete M Amiri, F Hatami, EM Golafshani Case Studies in Construction Materials 15, e00639, 2021 | 62 | 2021 |
| A feasibility study of BBP for predicting shear capacity of FRP reinforced concrete beams without stirrups EM Golafshani, A Ashour Advances in Engineering Software 97, 29-39, 2016 | 55 | 2016 |
| Predicting the mechanical properties of sustainable concrete containing waste foundry sand using multi-objective ANN approach EM Golafshani, A Behnood Construction and Building Materials 291, 123314, 2021 | 47 | 2021 |
| Predicting the dynamic modulus of asphalt mixture using machine learning techniques: An application of multi biogeography-based programming A Behnood, EM Golafshani Construction and Building Materials 266, 120983, 2021 | 47 | 2021 |
| Novel metaheuristic-based type-2 fuzzy inference system for predicting the compressive strength of recycled aggregate concrete EM Golafshani, A Behnood, SS Hosseinikebria, M Arashpour Journal of Cleaner Production 320, 128771, 2021 | 34 | 2021 |
| Predicting the compressive strength of self-compacting concrete containing fly ash using a hybrid artificial intelligence method EM Golafshani, G Pazouki Computers and Concrete, An International Journal 22 (4), 419-437, 2018 | 33 | 2018 |
| Predicting individual learning performance using machine‐learning hybridized with the teaching‐learning‐based optimization M Arashpour, EM Golafshani, R Parthiban, J Lamborn, A Kashani, H Li, ... Computer Applications in Engineering Education 31 (1), 83-99, 2023 | 32 | 2023 |
