| Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey D Karaboga, E Kaya Artificial Intelligence Review 52, 2263-2293, 2019 | 637 | 2019 |
| An adaptive and hybrid artificial bee colony algorithm (aABC) for ANFIS training D Karaboga, E Kaya Applied Soft Computing 49, 423-436, 2016 | 139 | 2016 |
| A survey on the artificial bee colony algorithm variants for binary, integer and mixed integer programming problems B Akay, D Karaboga, B Gorkemli, E Kaya Applied Soft Computing 106, 107351, 2021 | 82 | 2021 |
| A review on the studies employing artificial bee colony algorithm to solve combinatorial optimization problems E Kaya, B Gorkemli, B Akay, D Karaboga Engineering Applications of Artificial Intelligence 115, 105311, 2022 | 71 | 2022 |
| Training ANFIS by using the artificial bee colony algorithm D Karaboğa, E Kaya Turkish Journal of Electrical Engineering and Computer Sciences 25 (3), 1669 …, 2017 | 59 | 2017 |
| Training ANFIS by using an adaptive and hybrid artificial bee colony algorithm (aABC) for the identification of nonlinear static systems D Karaboga, E Kaya Arabian Journal for Science and Engineering 44 (4), 3531-3547, 2019 | 36 | 2019 |
| Estimation of number of foreign visitors with ANFIS by using ABC algorithm D Karaboga, E Kaya Soft Computing 24 (10), 7579-7591, 2020 | 35 | 2020 |
| Training ANFIS using artificial bee colony algorithm for nonlinear dynamic systems identification D Karaboga, E Kaya 2014 22nd Signal Processing and Communications Applications Conference (SIU …, 2014 | 31 | 2014 |
| A novel neural network training algorithm for the identification of nonlinear static systems: Artificial bee colony algorithm based on effective scout bee stage E Kaya, C Baştemur Kaya Symmetry 13 (3), 419, 2021 | 21 | 2021 |
| A new neural network training algorithm based on artificial bee colony algorithm for nonlinear system identification E Kaya Mathematics 10 (19), 3487, 2022 | 17 | 2022 |
| A comprehensive comparison of the performance of metaheuristic algorithms in neural network training for nonlinear system identification E Kaya Mathematics 10 (9), 1611, 2022 | 11 | 2022 |
| A novel approach based to neural network and flower pollination algorithm to predict number of COVID-19 cases CB Kaya, E Kaya Balkan Journal of Electrical and Computer Engineering 9 (4), 327-336, 2021 | 9 | 2021 |
| Training Neuro-Fuzzy by Using Meta-Heuristic Algorithms for MPPT. CB Kaya, E Kaya, G Gökkuş Computer Systems Science & Engineering 45 (1), 2023 | 8 | 2023 |
| Quick flower pollination algorithm (QFPA) and its performance on neural network training E Kaya Soft Computing 26 (18), 9729-9750, 2022 | 5 | 2022 |
| Evaluation of performance of adaptive and hybrid abc (aabc) algorithm in solution of numerical optimization problems D Karaboğa, E Kaya 2018 Innovations in Intelligent Systems and Applications Conference (ASYU), 1-5, 2018 | 5 | 2018 |
| Training of feed-forward neural networks by using optimization algorithms based on swarm-intelligent for maximum power point tracking E Kaya, C Baştemur Kaya, E Bendeş, S Atasever, B Öztürk, B Yazlık Biomimetics 8 (5), 402, 2023 | 2 | 2023 |
| Yüksek Boyutlu Nümerik Optimizasyon Problemlerinin Çözümünde Kelebek Optimizasyon Algoritmasının Performansının Değerlendirilmesi CB Kaya, E Kaya Mühendislik Bilimleri ve Araştırmaları Dergisi 4 (2), 296-303, 2022 | 1 | 2022 |
| Training neuro-fuzzy using flower pollination algorithm to predict number of COVID-19 cases: situation analysis for twenty countries C Baştemur Kaya, E Kaya Neural Computing and Applications, 1-29, 2024 | | 2024 |
| COVID-19 vaka sayısını tahmin etmek için yapay sinir ağı eğitiminde ABC algoritmasının bazı varyantlarının performanslarının karşılaştırılması E Kaya | | 2022 |
| Altın fiyatının tahmini için ABC algoritması, PSO ve FPA kullanılarak yapay sinir ağının eğitimi E Kaya | | 2022 |
