| Differential evolution for filter feature selection based on information theory and feature ranking E Hancer, B Xue, M Zhang Knowledge-Based Systems 140, 103-119, 2018 | 342 | 2018 |
| Pareto front feature selection based on artificial bee colony optimization E Hancer, B Xue, M Zhang, D Karaboga, B Akay Information Sciences 422, 462-479, 2018 | 321 | 2018 |
| A novel binary artificial bee colony algorithm based on genetic operators C Ozturk, E Hancer, D Karaboga Information Sciences 297, 154-170, 2015 | 190 | 2015 |
| Dynamic clustering with improved binary artificial bee colony algorithm C Ozturk, E Hancer, D Karaboga Applied Soft Computing 28, 69-80, 2015 | 187 | 2015 |
| A binary ABC algorithm based on advanced similarity scheme for feature selection E Hancer, B Xue, D Karaboga, M Zhang Applied Soft Computing 36, 334-348, 2015 | 178 | 2015 |
| A survey on feature selection approaches for clustering E Hancer, B Xue, M Zhang Artificial Intelligence Review, 1-27, 2020 | 140 | 2020 |
| A comprehensive survey of traditional, merge-split and evolutionary approaches proposed for determination of cluster number E Hancer, D Karaboga Swarm and Evolutionary Computation 32, 49-67, 2017 | 135 | 2017 |
| A multi-objective artificial bee colony approach to feature selection using fuzzy mutual information E Hancer, B Xue, M Zhang, D Karaboga, B Akay 2015 IEEE congress on evolutionary computation (CEC), 2420-2427, 2015 | 89 | 2015 |
| Differential evolution for feature selection: a fuzzy wrapper–filter approach E Hancer Soft Computing 23, 5233-5248, 2019 | 77 | 2019 |
| Artificial bee colony based image clustering method E Hancer, C Ozturk, D Karaboga 2012 IEEE congress on evolutionary computation, 1-5, 2012 | 73 | 2012 |
| Color image quantization: a short review and an application with artificial bee colony algorithm C Ozturk, E Hancer, D Karaboga Informatica 25 (3), 485-503, 2014 | 69 | 2014 |
| Improved clustering criterion for image clustering with artificial bee colony algorithm C Ozturk, E Hancer, D Karaboga Pattern Analysis and Applications 18, 587-599, 2015 | 68 | 2015 |
| A new multi-objective differential evolution approach for simultaneous clustering and feature selection E Hancer Engineering applications of artificial intelligence 87, 103307, 2020 | 66 | 2020 |
| Extraction of brain tumors from MRI images with artificial bee colony based segmentation methodology E Hancer, C Ozturk, D Karaboga 2013 8th International conference on electrical and electronics engineering …, 2013 | 58 | 2013 |
| A new approach to the reconstruction of contour lines extracted from topographic maps R Samet, E Hancer Journal of Visual Communication and Image Representation 23 (4), 642-647, 2012 | 44 | 2012 |
| Fuzzy kernel feature selection with multi-objective differential evolution algorithm E Hancer Connection Science 31 (4), 323-341, 2019 | 30 | 2019 |
| Automatic clustering with global best artificial bee colony algorithm C Ozturk, E Hancer, D KARABOĞA Journal of the Faculty of Engineering and Architecture of Gazi University 29 (4), 2014 | 27* | 2014 |
| New filter approaches for feature selection using differential evolution and fuzzy rough set theory E Hancer Neural Computing and Applications 32 (7), 2929-2944, 2020 | 24 | 2020 |
| Fuzzy filter cost-sensitive feature selection with differential evolution E Hancer, B Xue, M Zhang Knowledge-Based Systems 241, 108259, 2022 | 20 | 2022 |
| Advanced contour reconnection in scanned topographic maps E Hancer, R Samet 2011 5th International conference on application of information and …, 2011 | 20 | 2011 |
Dervis KarabogaComputer Engineering, Erciyes Universityerciyes.edu.tr üzerinde doğrulanmış e-posta adresine sahip
