| Modeling daily water temperature for rivers: comparison between adaptive neuro-fuzzy inference systems and artificial neural networks models S Zhu, S Heddam, EK Nyarko, M Hadzima-Nyarko, S Piccolroaz, S Wu Environmental Science and Pollution Research 26, 402-420, 2019 | 95 | 2019 |
| Modelling daily water temperature from air temperature for the Missouri River S Zhu, EK Nyarko, M Hadzima-Nyarko PeerJ 6, e4894, 2018 | 85 | 2018 |
| Flood-routing modeling with neural network optimized by social-based algorithm M Nikoo, F Ramezani, M Hadzima-Nyarko, EK Nyarko, M Nikoo Natural hazards 82, 1-24, 2016 | 81 | 2016 |
| Modelling the influence of waste rubber on compressive strength of concrete by artificial neural networks M Hadzima-Nyarko, EK Nyarko, N Ademović, I Miličević, T Kalman Šipoš Materials 12 (4), 561, 2019 | 75 | 2019 |
| Solving the parameter identification problem of mathematical models using genetic algorithms EK Nyarko, R Scitovski Applied mathematics and Computation 153 (3), 651-658, 2004 | 68 | 2004 |
| A modification of the DIRECT method for Lipschitz global optimization for a symmetric function R Grbić, EK Nyarko, R Scitovski Journal of Global Optimization 57, 1193-1212, 2013 | 65 | 2013 |
| A neural network based modelling and sensitivity analysis of damage ratio coefficient M Hadzima-Nyarko, EK Nyarko, D Morić Expert systems with applications 38 (10), 13405-13413, 2011 | 62 | 2011 |
| A nearest neighbor approach for fruit recognition in RGB-D images based on detection of convex surfaces EK Nyarko, I Vidović, K Radočaj, R Cupec Expert systems with applications 114, 454-466, 2018 | 55 | 2018 |
| Machine learning approaches for estimation of compressive strength of concrete M Hadzima-Nyarko, EK Nyarko, H Lu, S Zhu The European Physical Journal Plus 135 (8), 682, 2020 | 42 | 2020 |
| Determining the natural frequency of cantilever beams using ANN and heuristic search M Nikoo, M Hadzima-Nyarko, E Karlo Nyarko, M Nikoo Applied Artificial Intelligence 32 (3), 309-334, 2018 | 42 | 2018 |
| Assessing the performance of a suite of machine learning models for daily river water temperature prediction S Zhu, EK Nyarko, M Hadzima-Nyarko, S Heddam, S Wu PeerJ 7, e7065, 2019 | 40 | 2019 |
| Modeling of compressive strength of self-compacting rubberized concrete using machine learning M Kovačević, S Lozančić, EK Nyarko, M Hadzima-Nyarko Materials 14 (15), 4346, 2021 | 35 | 2021 |
| Place recognition based on matching of planar surfaces and line segments R Cupec, EK Nyarko, D Filko, A Kitanov, I Petrović The International Journal of Robotics Research 34 (4-5), 674-704, 2015 | 29 | 2015 |
| Wound measurement by RGB-D camera D Filko, R Cupec, EK Nyarko Machine vision and applications 29, 633-654, 2018 | 28 | 2018 |
| Modelling daily water temperature from air temperature for the Missouri River. PeerJ 6: e4894 S Zhu, EK Nyarko, M Hadzima-Nyarko | 24 | 2018 |
| Data preprocessing in data based process modeling D Slišković, R Grbić, EK Nyarko IFAC Proceedings Volumes 42 (19), 559-564, 2009 | 19 | 2009 |
| Detection, reconstruction and segmentation of chronic wounds using Kinect v2 sensor D Filko, R Cupec, EK Nyarko Procedia Computer Science 90, 151-156, 2016 | 18 | 2016 |
| Application of artificial intelligence methods for predicting the compressive strength of self-compacting concrete with class F fly ash M Kovačević, S Lozančić, EK Nyarko, M Hadzima-Nyarko Materials 15 (12), 4191, 2022 | 17 | 2022 |
| Fast 2.5 D Mesh Segmentation to Approximately Convex Surfaces. R Cupec, EK Nyarko, D Filko ECMR, 127-132, 2011 | 17 | 2011 |
| Optimization of public transport services to minimize passengers’ waiting times and maximize vehicles’ occupancy ratios I Hartmann Tolić, EK Nyarko, A Ceder Electronics 9 (2), 360, 2020 | 16 | 2020 |
