| Evapotranspiration evaluation models based on machine learning algorithms—A comparative study F Granata Agricultural Water Management 217, 303-315, 2019 | 305 | 2019 |
| Machine learning algorithms for the forecasting of wastewater quality indicators F Granata, S Papirio, G Esposito, R Gargano, G De Marinis Water 9 (2), 105, 2017 | 246 | 2017 |
| Support vector regression for rainfall-runoff modeling in urban drainage: A comparison with the EPA’s storm water management model F Granata, R Gargano, G De Marinis Water 8 (3), 69, 2016 | 196 | 2016 |
| Groundwater level prediction in Apulia region (Southern Italy) using NARX neural network F Di Nunno, F Granata Environmental Research 190, 110062, 2020 | 144 | 2020 |
| Groundwater level prediction using machine learning algorithms in a drought-prone area QB Pham, M Kumar, F Di Nunno, A Elbeltagi, F Granata, ARMT Islam, ... Neural Computing and Applications 34 (13), 10751-10773, 2022 | 140 | 2022 |
| Forecasting evapotranspiration in different climates using ensembles of recurrent neural networks F Granata, F Di Nunno Agricultural Water Management 255, 107040, 2021 | 139 | 2021 |
| Simultaneous nitrification, denitrification and phosphorus removal in a continuous-flow moving bed biofilm reactor alternating microaerobic and aerobic conditions F Iannacone, F Di Capua, F Granata, R Gargano, G Esposito Bioresource technology 310, 123453, 2020 | 126 | 2020 |
| Stacked machine learning algorithms and bidirectional long short-term memory networks for multi-step ahead streamflow forecasting: A comparative study F Granata, F Di Nunno, G de Marinis Journal of Hydrology 613, 128431, 2022 | 109 | 2022 |
| Hydraulics of circular drop manholes F Granata, G de Marinis, R Gargano, WH Hager Journal of Irrigation and Drainage Engineering 137 (2), 102-111, 2011 | 99 | 2011 |
| Artificial intelligence based approaches to evaluate actual evapotranspiration in wetlands F Granata, R Gargano, G de Marinis Science of The Total Environment 703, 135653, 2020 | 98 | 2020 |
| Intravoxel incoherent motion (IVIM) in diffusion-weighted imaging (DWI) for Hepatocellular carcinoma: correlation with histologic grade V Granata, R Fusco, O Catalano, B Guarino, F Granata, F Tatangelo, ... Oncotarget 7 (48), 79357, 2016 | 95 | 2016 |
| Shortcut nitrification-denitrification and biological phosphorus removal in acetate-and ethanol-fed moving bed biofilm reactors under microaerobic/aerobic conditions F Iannacone, F Di Capua, F Granata, R Gargano, G Esposito Bioresource Technology 330, 124958, 2021 | 93 | 2021 |
| Effect of carbon-to-nitrogen ratio on simultaneous nitrification denitrification and phosphorus removal in a microaerobic moving bed biofilm reactor F Iannacone, F Di Capua, F Granata, R Gargano, F Pirozzi, G Esposito Journal of Environmental Management 250, 109518, 2019 | 78 | 2019 |
| Artificial Intelligence models for prediction of the tide level in Venice F Granata, F Di Nunno Stochastic Environmental Research and Risk Assessment 35 (12), 2537-2548, 2021 | 73 | 2021 |
| Early radiological assessment of locally advanced pancreatic cancer treated with electrochemotherapy V Granata, R Fusco, SV Setola, M Piccirillo, M Leongito, R Palaia, ... World Journal of Gastroenterology 23 (26), 4767, 2017 | 66 | 2017 |
| Multidetector computer tomography in the pancreatic adenocarcinoma assessment: an update V Granata, R Fusco, O Catalano, SV Setola, E de Lutio di Castelguidone, ... Infectious agents and cancer 11, 1-7, 2016 | 62 | 2016 |
| Neuroforecasting of daily streamflows in the UK for short-and medium-term horizons: A novel insight F Granata, F Di Nunno Journal of Hydrology 624, 129888, 2023 | 59 | 2023 |
| A stacked machine learning model for multi-step ahead prediction of lake surface water temperature F Di Nunno, S Zhu, M Ptak, M Sojka, F Granata Science of the Total Environment 890, 164323, 2023 | 54 | 2023 |
| Machine learning models for spring discharge forecasting F Granata, M Saroli, G de Marinis, R Gargano Geofluids 2018 (1), 8328167, 2018 | 54 | 2018 |
| Prediction of spring flows using nonlinear autoregressive exogenous (NARX) neural network models F Di Nunno, F Granata, R Gargano, G de Marinis Environmental Monitoring and Assessment 193 (6), 350, 2021 | 51 | 2021 |
Fabio DI NUNNOUniversity of Cassino and Southern LazioEmail verificata su unicas.it
