| Comparative analysis of GMDH neural network based on genetic algorithm and particle swarm optimization in stable channel design S Shaghaghi, H Bonakdari, A Gholami, I Ebtehaj, M Zeinolabedini Applied Mathematics and Computation 313, 271-286, 2017 | 100 | 2017 |
| Experimental and numerical study on velocity fields and water surface profile in a strongly-curved 90 open channel bend A Gholami, A Akbar Akhtari, Y Minatour, H Bonakdari, AA Javadi Engineering Applications of Computational Fluid Mechanics 8 (3), 447-461, 2014 | 83 | 2014 |
| Uncertainty analysis of intelligent model of hybrid genetic algorithm and particle swarm optimization with ANFIS to predict threshold bank profile shape based on digital laser … A Gholami, H Bonakdari, I Ebtehaj, M Mohammadian, B Gharabaghi, ... Measurement 121, 294-303, 2018 | 72 | 2018 |
| Simulation of open channel bend characteristics using computational fluid dynamics and artificial neural networks A Gholami, H Bonakdari, AH Zaji, AA Akhtari Engineering Applications of Computational Fluid Mechanics 9 (1), 355-369, 2015 | 64 | 2015 |
| Developing an expert group method of data handling system for predicting the geometry of a stable channel with a gravel bed A Gholami, H Bonakdari, I Ebtehaj, S Shaghaghi, F Khoshbin Earth Surface Processes and Landforms 42 (10), 1460-1471, 2017 | 55 | 2017 |
| Design of modified structure multi-layer perceptron networks based on decision trees for the prediction of flow parameters in 90 open-channel bends A Gholami, H Bonakdari, AH Zaji, S Ajeel Fenjan, AA Akhtari Engineering Applications of Computational Fluid Mechanics 10 (1), 193-208, 2016 | 48 | 2016 |
| A methodological approach of predicting threshold channel bank profile by multi-objective evolutionary optimization of ANFIS A Gholami, H Bonakdari, I Ebtehaj, B Gharabaghi, SR Khodashenas, ... Engineering Geology 239, 298-309, 2018 | 46 | 2018 |
| Reliable method of determining stable threshold channel shape using experimental and gene expression programming techniques A Gholami, H Bonakdari, M Zeynoddin, I Ebtehaj, B Gharabaghi, ... Neural Computing and Applications 31, 5799-5817, 2019 | 44 | 2019 |
| Design of an adaptive neuro-fuzzy computing technique for predicting flow variables in a 90 sharp bend A Gholami, H Bonakdari, I Ebtehaj, AA Akhtari Journal of Hydroinformatics 19 (4), 572-585, 2017 | 43 | 2017 |
| Predicting stable alluvial channel profiles using emotional artificial neural networks A Gholami, H Bonakdari, P Samui, M Mohammadian, B Gharabaghi Applied Soft Computing 78, 420-437, 2019 | 40 | 2019 |
| Improving the performance of multi-layer perceptron and radial basis function models with a decision tree model to predict flow variables in a sharp 90 bend A Gholami, H Bonakdari, AH Zaji, DG Michelson, AA Akhtari Applied Soft Computing 48, 563-583, 2016 | 40 | 2016 |
| Predicting the geometry of regime rivers using M5 model tree, multivariate adaptive regression splines and least square support vector regression methods S Shaghaghi, H Bonakdari, A Gholami, O Kisi, A Binns, B Gharabaghi International Journal of River Basin Management 17 (3), 333-352, 2019 | 33 | 2019 |
| Predicting the velocity field in a 90 open channel bend using a gene expression programming model A Gholami, H Bonakdari, AH Zaji, AA Akhtari, SR Khodashenas Flow measurement and instrumentation 46, 189-192, 2015 | 31 | 2015 |
| Flow variables prediction using experimental, computational fluid dynamic and artificial neural network models in a sharp bend A Gholami, H Bonakdari, SA Fenjan, AA Akhtari International Journal of Engineering 29 (1), 14-22, 2016 | 27 | 2016 |
| Stable alluvial channel design using evolutionary neural networks S Shaghaghi, H Bonakdari, A Gholami, O Kisi, J Shiri, AD Binns, ... Journal of hydrology 566, 770-782, 2018 | 24 | 2018 |
| A comparison of artificial intelligence-based classification techniques in predicting flow variables in sharp curved channels A Gholami, H Bonakdari, AH Zaji, AA Akhtari Engineering with Computers 36, 295-324, 2020 | 23 | 2020 |
| New radial basis function network method based on decision trees to predict flow variables in a curved channel A Gholami, H Bonakdari, AH Zaji, SA Fenjan, AA Akhtari Neural Computing and Applications 30, 2771-2785, 2018 | 23 | 2018 |
| Assessment of geomorphological bank evolution of the alluvial threshold rivers based on entropy concept parameters A Gholami, H Bonakdari, M Mohammadian, AH Zaji, B Gharabaghi Hydrological sciences journal 64 (7), 856-872, 2019 | 22 | 2019 |
| A combination of computational fluid dynamics, artificial neural network, and support vectors machines models to predict flow variables in curved channel A Gholami, H Bonakdari, AA Akhtari, I Ebtehaj Scientia Iranica 26 (2), 726-741, 2019 | 19 | 2019 |
| Uncertainty analysis of shear stress estimation in circular channels by Tsallis entropy A Kazemian-Kale-Kale, H Bonakdari, A Gholami, ZS Khozani, AA Akhtari, ... Physica A: Statistical Mechanics and its Applications 510, 558-576, 2018 | 19 | 2018 |
Hossein BonakdariAssociate ProfessorVerified email at fsaa.ulaval.ca
