| Coastal water quality prediction based on machine learning with feature interpretation and spatio-temporal analysis L Grbčić, S Družeta, G Mauša, T Lipić, DV Lušić, M Alvir, I Lučin, A Sikirica, ... Environmental modelling & software 155, 105458, 2022 | 39 | 2022 |
| Temporal variations analyses and predictive modeling of microbiological seawater quality DV Lušić, L Kranjčević, S Maćešić, D Lušić, S Jozić, Ž Linšak, L Bilajac, ... Water research 119, 160-170, 2017 | 38 | 2017 |
| NS1: a key protein in the “game” between influenza a virus and host in innate immunity Z Ji, X Wang, X Liu Frontiers in Cellular and Infection Microbiology 11, 670177, 2021 | 35 | 2021 |
| Water supply network pollution source identification by random forest algorithm L Grbčić, I Lučin, L Kranjčević, S Družeta Journal of Hydroinformatics 22 (6), 1521-1535, 2020 | 32 | 2020 |
| Numerical analysis of Wells turbine for wave power conversion Z Čarija, L Kranjčević, V Banić, M Čavrak Engineering Review: Međunarodni časopis namijenjen publiciranju originalnih …, 2012 | 28 | 2012 |
| Machine learning and simulation-optimization coupling for water distribution network contamination source detection L Grbčić, L Kranjčević, S Družeta Sensors 21 (4), 1157, 2021 | 24 | 2021 |
| Grid type and turbulence model influence on propeller characteristics prediction A Sikirica, Z Čarija, L Kranjčević, I Lučin Journal of Marine Science and Engineering 7 (10), 374, 2019 | 24 | 2019 |
| A machine learning-based algorithm for water network contamination source localization L Grbčić, I Lučin, L Kranjčević, S Družeta Sensors 20 (9), 2613, 2020 | 22 | 2020 |
| Machine learning based surrogate models for microchannel heat sink optimization A Sikirica, L Grbčić, L Kranjčević Applied Thermal Engineering 222, 119917, 2023 | 21 | 2023 |
| Groundwater nitrate pollution sources assessment for contaminated wellfield M Šrajbek, L Kranjčević, I Kovač, R Biondić Water 14 (2), 255, 2022 | 16 | 2022 |
| Assessment of head loss coefficients for water turbine intake trash-racks by numerical modeling I Lučin, Z Čarija, L Grbčić, L Kranjčević Journal of advanced research 21, 109-119, 2020 | 15 | 2020 |
| Machine-learning classification of a number of contaminant sources in an urban water network I Lučin, L Grbčić, Z Čarija, L Kranjčević Sensors 21 (1), 245, 2021 | 14 | 2021 |
| Improvements of semi-implicit schemes for hyperbolic balance laws applied on open channel flow equations B Crnković, N Črnjarić-Žic, L Kranjčević Computers & mathematics with applications 58 (2), 292-309, 2009 | 14 | 2009 |
| Efficient double-tee junction mixing assessment by machine learning L Grbčić, L Kranjčević, S Družeta, I Lučin Water 12 (1), 238, 2020 | 13 | 2020 |
| Experimental and numerical investigation of mixing phenomena in double-tee junctions L Grbčić, L Kranjčević, I Lučin, Z Čarija Water 11 (6), 1198, 2019 | 12 | 2019 |
| Impacts of atmospheric and anthropogenic factors on microbiological pollution of the recreational coastal beaches neighboring shipping ports R Kraus, V Baljak, D Vukić Lušić, L Kranjčević, A Cenov, M Glad, ... International journal of environmental research and public health 19 (14), 8552, 2022 | 9 | 2022 |
| Cavitation model calibration using machine learning assisted workflow A Sikirica, Z Čarija, I Lučin, L Grbčić, L Kranjčević Mathematics 8 (12), 2107, 2020 | 8 | 2020 |
| Contamination source detection in water distribution networks L Kranjčević, M Čavrak, M Šestan Engineering Review, 2010 | 8 | 2010 |
| Large Eddy Simulation of turbulent fluid mixing in double-tee junctions L Grbčić, L Kranjčević, I Lučin, A Sikirica Ain Shams Engineering Journal 12 (1), 789-797, 2021 | 7 | 2021 |
| Evaluation of the efficacy of cancer drugs by using the second largest eigenvalue of metabolic cancer pathways D Tomić, K Skala, L Kranjčević, B Pirkić, S Štifter, I Šmit Journal of Computer Science & Systems Biology 11 (3), 240-248, 2018 | 7 | 2018 |
