| Sea water level forecasting using genetic programming and comparing the performance with artificial neural networks MA Ghorbani, R Khatibi, A Aytek, O Makarynskyy, J Shiri Computers & geosciences 36 (5), 620-627, 2010 | 182 | 2010 |
| Groundwater vulnerability indices conditioned by supervised intelligence committee machine (SICM) AA Nadiri, M Gharekhani, R Khatibi, S Sadeghfam, AA Moghaddam Science of the Total Environment 574, 691-706, 2017 | 131 | 2017 |
| Investigating chaos in river stage and discharge time series R Khatibi, B Sivakumar, MA Ghorbani, O Kisi, K Koçak, DF Zadeh Journal of Hydrology 414, 108-117, 2012 | 129 | 2012 |
| Identification problem of open-channel friction parameters RH Khatibi, JJR Williams, PR Wormleaton Journal of Hydraulic Engineering 123 (12), 1078-1088, 1997 | 95 | 1997 |
| Modelling groundwater level variations by learning from multiple models using fuzzy logic AA Nadiri, K Naderi, R Khatibi, M Gharekhani Hydrological sciences journal 64 (2), 210-226, 2019 | 94 | 2019 |
| Assessment of groundwater vulnerability using supervised committee to combine fuzzy logic models AA Nadiri, M Gharekhani, R Khatibi, AA Moghaddam Environmental Science and Pollution Research 24, 8562-8577, 2017 | 92 | 2017 |
| Comparison of three artificial intelligence techniques for discharge routing R Khatibi, MA Ghorbani, MH Kashani, O Kisi Journal of hydrology 403 (3-4), 201-212, 2011 | 91 | 2011 |
| Relative importance of parameters affecting wind speed prediction using artificial neural networks MA Ghorbani, R Khatibi, B Hosseini, M Bilgili Theoretical and Applied Climatology 114, 107-114, 2013 | 82 | 2013 |
| Modeling river discharge time series using support vector machine and artificial neural networks MA Ghorbani, R Khatibi, A Goel, MH FazeliFard, A Azani Environmental Earth Sciences 75, 1-13, 2016 | 80 | 2016 |
| Mapping specific vulnerability of multiple confined and unconfined aquifers by using artificial intelligence to learn from multiple DRASTIC frameworks S Nadiri, A.A., Sedghia, Z., Khatibi, R., Sadeghfam Journal of Environmental Management 227, 415-428, 2018 | 79 | 2018 |
| Mapping vulnerability of multiple aquifers using multiple models and fuzzy logic to objectively derive model structures AA Nadiri, Z Sedghi, R Khatibi, M Gharekhani Science of the Total Environment 593, 75-90, 2017 | 79 | 2017 |
| Learning from multiple models using artificial intelligence to improve model prediction accuracies: application to river flows MA Ghorbani, R Khatibi, V Karimi, ZM Yaseen, M Zounemat-Kermani Water resources management 32, 4201-4215, 2018 | 73 | 2018 |
| Groundwater DRASTIC vulnerability mapping by unsupervised and supervised techniques using a modelling strategy in two levels AA Nadiri, H Norouzi, R Khatibi, M Gharekhani Journal of hydrology 574, 744-759, 2019 | 58 | 2019 |
| Mapping groundwater potential field using catastrophe fuzzy membership functions and Jenks optimization method: a case study of Maragheh-Bonab plain, Iran S Sadeghfam, Y Hassanzadeh, AA Nadiri, R Khatibi Environmental Earth Sciences 75, 1-19, 2016 | 57 | 2016 |
| Experimental studies on scour of supercritical flow jets in upstream of screens and modelling scouring dimensions using artificial intelligence to combine multiple models (AIMM) S Sadeghfam, R Daneshfaraz, R Khatibi, O Minaei Journal of Hydroinformatics 21 (5), 893-907, 2019 | 55 | 2019 |
| Chaos-based multigene genetic programming: a new hybrid strategy for river flow forecasting MA Ghorbani, R Khatibi, AD Mehr, H Asadi Journal of hydrology 562, 455-467, 2018 | 54 | 2018 |
| Stream flow predictions using nature-inspired Firefly Algorithms and a Multiple Model strategy – Directions of innovation towards next generation practices; Journal of Advanced … FAP R. Khatibia, M.A. Ghorbani Advanced Engineering Informatics 34, Pages 80–89, 2017 | 53 | 2017 |
| Modelling energy dissipation over stepped-gabion weirs by artificial intelligence R Khatibi, F Salmasi, MA Ghorbani, H Asadi Water resources management 28, 1807-1821, 2014 | 53 | 2014 |
| Mapping aquifer vulnerability indices using artificial intelligence-running multiple frameworks (AIMF) with supervised and unsupervised learning AA Nadiri, M Gharekhani, R Khatibi Water resources management 32, 3023-3040, 2018 | 48 | 2018 |
| Introducing a new framework for mapping subsidence vulnerability indices (SVIs): ALPRIFT AA Nadiri, Z Taheri, R Khatibi, G Barzegari, K Dideban Science of the Total Environment 628, 1043-1057, 2018 | 48 | 2018 |
