| Support vector machine applications in the field of hydrology: a review NS Raghavendra, PC Deka Applied soft computing 19, 372-386, 2014 | 764 | 2014 |
| Irrigation induced salinity and sodicity hazards on soil and groundwater: An overview of its causes, impacts and mitigation strategies A Mohanavelu, SR Naganna, N Al-Ansari Agriculture 11 (10), 983, 2021 | 157 | 2021 |
| Wavelet coupled MARS and M5 Model Tree approaches for groundwater level forecasting M Rezaie-balf, SR Naganna, A Ghaemi, PC Deka Journal of hydrology 553, 356-373, 2017 | 142 | 2017 |
| Dew point temperature estimation: application of artificial intelligence model integrated with nature-inspired optimization algorithms SR Naganna, PC Deka, MA Ghorbani, SM Biazar, N Al-Ansari, ... Water 11 (4), 742, 2019 | 93 | 2019 |
| Investigation of concrete produced using recycled aluminium dross for hot weather concreting conditions G Mailar, NS Raghavendra, BM Sreedhara, DS Manu, P Hiremath, ... Resource-Efficient Technologies 2 (2), 68-80, 2016 | 79 | 2016 |
| Hourly river flow forecasting: application of emotional neural network versus multiple machine learning paradigms ZM Yaseen, SR Naganna, Z Sa’adi, P Samui, MA Ghorbani, SQ Salih, ... Water Resources Management 34, 1075-1091, 2020 | 77 | 2020 |
| Forecasting monthly groundwater level fluctuations in coastal aquifers using hybrid Wavelet packet–Support vector regression N Sujay Raghavendra, PC Deka Cogent Engineering 2 (1), 999414, 2015 | 70 | 2015 |
| Sustainable development and management of groundwater resources in mining affected areas: a review NS Raghavendra, PC Deka Procedia Earth and Planetary Science 11, 598-604, 2015 | 62 | 2015 |
| Eco-concrete for sustainability: utilizing aluminium dross and iron slag as partial replacement materials S Javali, AR Chandrashekar, SR Naganna, DS Manu, P Hiremath, ... Clean Technologies and Environmental Policy 19, 2291-2304, 2017 | 56 | 2017 |
| Multiple AI model integration strategy—application to saturated hydraulic conductivity prediction from easily available soil properties MH Kashani, MA Ghorbani, M Shahabi, SR Naganna, L Diop Soil and Tillage Research 196, 104449, 2020 | 53 | 2020 |
| Hybrid wavelet packet machine learning approaches for drought modeling P Das, SR Naganna, PC Deka, J Pushparaj Environmental Earth Sciences 79 (10), 221, 2020 | 52 | 2020 |
| Factors influencing streambed hydraulic conductivity and their implications on stream–aquifer interaction: a conceptual review SR Naganna, PC Deka, S Ch, WF Hansen Environmental Science and Pollution Research 24, 24765-24789, 2017 | 52 | 2017 |
| On the evaluation of the gradient tree boosting model for groundwater level forecasting SR Naganna, BH Beyaztas, N Bokde, AM Armanuos Knowledge-Based Engineering and Sciences 1 (01), 48-57, 2020 | 47 | 2020 |
| Enhancing streamflow forecasting using the augmenting ensemble procedure coupled machine learning models: case study of Aswan High Dam M Rezaie-Balf, SR Naganna, O Kisi, A El-Shafie Hydrological Sciences Journal 64 (13), 1629-1646, 2019 | 46 | 2019 |
| Multistep ahead groundwater level time-series forecasting using Gaussian process regression and ANFIS NS Raghavendra, PC Deka Advanced Computing and Systems for Security: Volume 2, 289-302, 2016 | 39 | 2016 |
| Sourcing CHIRPS precipitation data for streamflow forecasting using intrinsic time-scale decomposition based machine learning models M Wang, M Rezaie-Balf, SR Naganna, ZM Yaseen Hydrological Sciences Journal 66 (9), 1437-1456, 2021 | 29 | 2021 |
| Spatial variability of ground water quality: a case study of Udupi district, Karnataka State, India BV Deepika, CR Ramakrishnaiah, SR Naganna Journal of Earth System Science 129, 1-20, 2020 | 29 | 2020 |
| Streambed pollution: A comprehensive review of its sources, eco-hydro-geo-chemical impacts, assessment, and mitigation strategies A Mohanavelu, S Shrivastava, SR Naganna Chemosphere 300, 134589, 2022 | 26 | 2022 |
| Comparative evaluation of deep learning and machine learning in modelling pan evaporation using limited inputs O Kisi, A Mirboluki, SR Naganna, A Malik, A Kuriqi, M Mehraein Hydrological Sciences Journal 67 (9), 1309-1327, 2022 | 21 | 2022 |
| Application of gradient tree boosting regressor for the prediction of scour depth around bridge piers BM Sreedhara, AP Patil, J Pushparaj, G Kuntoji, SR Naganna Journal of Hydroinformatics 23 (4), 849-863, 2021 | 20 | 2021 |
Sreedhara B MarulasiddappaDept. of Civil Engineering, Siddaganga Institute of Technology, Tumakuru - 572103Email verificata su sit.ac.in