| Assessment of input variables determination on the SVM model performance using PCA, Gamma test, and forward selection techniques for monthly stream flow prediction R Noori, AR Karbassi, A Moghaddamnia, D Han, MH Zokaei-Ashtiani, ... Journal of hydrology 401 (3-4), 177-189, 2011 | 424 | 2011 |
| Evaporation estimation using artificial neural networks and adaptive neuro-fuzzy inference system techniques A Moghaddamnia, MG Gousheh, J Piri, S Amin, D Han Advances in Water Resources 32 (1), 88-97, 2009 | 384 | 2009 |
| Daily suspended sediment load prediction using artificial neural networks and support vector machines EK Lafdani, A Moghaddam Nia, A Ahmadi Journal of Hydrology 478, 50-62, 2013 | 277 | 2013 |
| Application of ANN and ANFIS models for reconstructing missing flow data MT Dastorani, A Moghaddam Nia, J Piri, M Rico-Ramirez Environmental Monitoring and Assessment 166 (1), 421–434, 2010 | 198 | 2010 |
| Comparison of LLR, MLP, Elman, NNARX and ANFIS Models—with a case study in solar radiation estimation A Moghaddam Nia, R Remesan, MH Kashani, M Mohammadi, D Han, ... Journal of Atmospheric and Solar-Terrestrial Physics 71 (8), 975-982, 2009 | 172 | 2009 |
| Application of several data-driven techniques for predicting groundwater level B Shirmohammadi, M Vafakhah, V Moosavi, A Moghaddam Nia Water Resources Management 27 (2), 419-432, 2013 | 167 | 2013 |
| Daily pan evaporation modeling in a hot and dry climate J Piri, S Amin, A Moghaddam Nia, A Keshavarz, D Han, R Remesan Journal of Hydrologic Engineering 14 (8), 803-811, 2009 | 140 | 2009 |
| Dust storms impacts on air pollution and public health under hot and dry climate A Miri, H Ahmadi, A Ghanbari, A Moghaddam Nia Int. J. Energy Environ 2 (1), 101-105, 2007 | 137 | 2007 |
| Intermittent streamflow forecasting by using several data driven techniques O Kisi, A Moghaddam Nia, MG Gosheh, MRJ Tajabadi, A Ahmadi Water resources management 26 (2), 457-474, 2012 | 121 | 2012 |
| Performance comparison of an LSTM-based deep learning model versus conventional machine learning algorithms for streamflow forecasting M Rahimzad, A Moghaddam Nia, H Zolfonoon, J Soltani, ... Water Resources Management 35 (12), 4167-4187, 2021 | 97 | 2021 |
| Identification of homogeneous regions for regionalization of watersheds by two-level self-organizing feature maps F Farsadnia, MR Kamrood, A Moghaddam Nia, R Modarres, MT Bray, ... Journal of Hydrology 509, 387-397, 2014 | 96 | 2014 |
| Performance evaluation of ANN and ANFIS models for estimating garlic crop evapotranspiration HZ Abyaneh, A Moghaddam Nia, MB Varkeshi, S Marofi, O Kisi Journal of Irrigation and Drainage Engineering 137 (5), 280-286, 2010 | 71 | 2010 |
| A cost-effective and efficient framework to determine water quality monitoring network locations H Alilou, A Moghaddam Nia, H Keshtkar, D Han, M Bray Science of the total environment 624, 283-293, 2018 | 69 | 2018 |
| Application of “panel-data” modeling to predict groundwater levels in the Neishaboor Plain, Iran A Izady, K Davary, A Alizadeh, B Ghahraman, M Sadeghi, ... Hydrogeology Journal 20 (3), 435-447, 2012 | 66 | 2012 |
| Assessment of drought risk index using drought hazard and vulnerability indices M Nasrollahi, H Khosravi, A Moghaddamnia, A Malekian, S Shahid Arabian Journal of Geosciences 11, 1-12, 2018 | 65 | 2018 |
| Comparison of ANFIS, ANN, GARCH and ARIMA techniques to exchange rate forecasting SM Fahimifard, M Homayounifar, M Sabouhi, AR Moghaddam Nia Journal of Applied Sciences 9 (20), 3641-3651, 2009 | 63 | 2009 |
| Application of NN-ARX model to predict groundwater levels in the Neishaboor Plain, Iran A Izady, K Davary, A Alizadeh, A Moghaddam Nia, AN Ziaei, ... Water resources management 27 (14), 4773-4794, 2013 | 55 | 2013 |
| Dust storm frequency after the 1999 drought in the Sistan region, Iran A Miri, A Moghaddamnia, A Pahlavanravi, N Panjehkeh Climate Research 41 (1), 83-90, 2010 | 51 | 2010 |
| Dust Storm Prediction Using ANNs Technique (A Case Study: Zabol City) 1 MR Jamalizadeh, A Moghaddam Nia, J Piri, V Arbabi, M Homayounifar, ... | 46 | 2008 |
| Danandeh Mehr A, Kwon HH (2021) Performance comparison of an LSTM-based deep learning model versus conventional machine learning algorithms for streamflow forecasting M Rahimzad, A Moghaddam Nia, H Zolfonoon, J Soltani Water Resources Management 35 (12), 4167-4187, 0 | 44 | |
Dawei HanProfessor of Hydroinformatics, University of BristolVerified email at bristol.ac.uk
