| Multimodal optimization by means of a topological species conservation algorithm C Stoean, M Preuss, R Stoean, D Dumitrescu IEEE Transactions on Evolutionary Computation 14 (6), 842-864, 2010 | 155 | 2010 |
| Performance of a novel chaotic firefly algorithm with enhanced exploration for tackling global optimization problems: Application for dropout regularization N Bacanin, R Stoean, M Zivkovic, A Petrovic, TA Rashid, T Bezdan Mathematics 9 (21), 2705, 2021 | 115 | 2021 |
| Modeling medical decision making by support vector machines, explaining by rules of evolutionary algorithms with feature selection R Stoean, C Stoean Expert Systems with Applications 40 (7), 2677-2686, 2013 | 110 | 2013 |
| Deep architectures for long-term stock price prediction with a heuristic-based strategy for trading simulations C Stoean, W Paja, R Stoean, A Sandita PloS one 14 (10), e0223593, 2019 | 67 | 2019 |
| Evolutionary-driven support vector machines for determining the degree of liver fibrosis in chronic hepatitis C R Stoean, C Stoean, M Lupsor, H Stefanescu, R Badea Artificial intelligence in medicine 51 (1), 53-65, 2011 | 65 | 2011 |
| Analysis on the potential of an EA–surrogate modelling tandem for deep learning parametrization: an example for cancer classification from medical images R Stoean Neural Computing and Applications 32 (2), 313-322, 2020 | 51 | 2020 |
| Support vector machines and evolutionary algorithms for classification C Stoean, R Stoean Single or Together, 2014 | 49 | 2014 |
| On the benefits of using metaheuristics in the hyperparameter tuning of deep learning models for energy load forecasting N Bacanin, C Stoean, M Zivkovic, M Rakic, R Strulak-Wójcikiewicz, ... Energies 16 (3), 1434, 2023 | 46 | 2023 |
| Feature selection for a cooperative coevolutionary classifier in liver fibrosis diagnosis C Stoean, R Stoean, M Lupsor, H Stefanescu, R Badea Computers in biology and medicine 41 (4), 238-246, 2011 | 42 | 2011 |
| Disburdening the species conservation evolutionary algorithm of arguing with radii CL Stoean, M Preuss, R Stoean, D Dumitrescu Proceedings of the 9th annual conference on Genetic and evolutionary …, 2007 | 35 | 2007 |
| Metaheuristic-based hyperparameter tuning for recurrent deep learning: application to the prediction of solar energy generation C Stoean, M Zivkovic, A Bozovic, N Bacanin, R Strulak-Wójcikiewicz, ... Axioms 12 (3), 266, 2023 | 33 | 2023 |
| Surface study of inhibitor films formed by polyvinyl alcohol and silver nanoparticles on stainless steel in hydrochloric acid solution using convolutional neural networks A Samide, C Stoean, R Stoean Applied Surface Science 475, 1-5, 2019 | 33 | 2019 |
| Ensemble of classifiers for length of stay prediction in colorectal cancer R Stoean, C Stoean, A Sandita, D Ciobanu, C Mesina Advances in Computational Intelligence: 13th International Work-Conference …, 2015 | 32 | 2015 |
| Elitist generational genetic chromodynamics-a new radii-based evolutionary algorithm for multimodal optimization C Stoean, M Preuss, R Gorunescu, D Dumitrescu 2005 IEEE Congress on Evolutionary Computation 2, 1839-1846, 2005 | 31 | 2005 |
| Adaptation of deep convolutional neural networks for cancer grading from histopathological images S Postavaru, R Stoean, C Stoean, GJ Caparros Advances in Computational Intelligence: 14th International Work-Conference …, 2017 | 30 | 2017 |
| Evolutionary support vector regression machines R Stoean, D Dumitrescu, M Preuss, C Stoean 2006 Eighth International Symposium on Symbolic and Numeric Algorithms for …, 2006 | 30 | 2006 |
| Niching foundations: basin identification on fixed-property generated landscapes M Preuss, C Stoean, R Stoean Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011 | 29 | 2011 |
| Svm-based cancer grading from histopathological images using morphological and topological features of glands and nuclei C Stoean, R Stoean, A Sandita, D Ciobanu, C Mesina, CL Gruia Intelligent interactive multimedia systems and services 2016, 145-155, 2016 | 28 | 2016 |
| Automated detection of presymptomatic conditions in Spinocerebellar Ataxia type 2 using Monte Carlo dropout and deep neural network techniques with electrooculogram signals C Stoean, R Stoean, M Atencia, M Abdar, L Velázquez-Pérez, A Khosravi, ... Sensors 20 (11), 3032, 2020 | 27 | 2020 |
| Support vector machine learning with an evolutionary engine R Stoean, M Preuss, C Stoean, E El-Darzi, D Dumitrescu Journal of the Operational Research Society 60 (8), 1116-1122, 2009 | 26 | 2009 |
