Emmanuel Karlo Nyarko
Emmanuel Karlo Nyarko
Faculty of Electrical Engineering, Computer Science and Information Technology, Osijek
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Cited by
Cited by
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
Modelling daily water temperature from air temperature for the Missouri River
S Zhu, EK Nyarko, M Hadzima-Nyarko
PeerJ 6, e4894, 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
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
Solving the parameter identification problem of mathematical models using genetic algorithms
EK Nyarko, R Scitovski
Applied mathematics and Computation 153 (3), 651-658, 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
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
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
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
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
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
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
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
Wound measurement by RGB-D camera
D Filko, R Cupec, EK Nyarko
Machine vision and applications 29, 633-654, 2018
Modelling daily water temperature from air temperature for the Missouri River. PeerJ 6: e4894
S Zhu, EK Nyarko, M Hadzima-Nyarko
Detection, reconstruction and segmentation of chronic wounds using Kinect v2 sensor
D Filko, R Cupec, EK Nyarko
Procedia Computer Science 90, 151-156, 2016
Data preprocessing in data based process modeling
D Slišković, R Grbić, EK Nyarko
IFAC Proceedings Volumes 42 (19), 559-564, 2009
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
Short-term forecasting of electricity consumption using artificial neural networks-an overview
I Barić, R Grbić, EK Nyarko
2019 42nd International Convention on Information and Communication …, 2019
Fast 2.5 D Mesh Segmentation to Approximately Convex Surfaces.
R Cupec, EK Nyarko, D Filko
ECMR, 127-132, 2011
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