Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Conference Object Citation - WoS: 1Citation - Scopus: 1Dengesiz Epilepsi Veri Seti İçin Sınıflandırmada Farklı SMOTE Yöntemlerinin Etkileri(Institute of Electrical and Electronics Engineers Inc., 2025) Calis, Ahmet Gokay; Ergezer, HalitIn this study, the effects of different SMOTE methods on machine learning algorithms for the imbalanced epilepsy dataset were investigated. After filtering, the imbalanced dataset was balanced with 5 different SMOTE methods and classified with various machine learning algorithms. Coarse-K-Nearest Neighbor, Bagged Trees, and Artificial Neural Networks models were evaluated in epilepsy detection. The performance of these different models was compared with Matthews Correlation Coefficient (MCC) and F1 Score metrics. The results showed that the Borderline-SMOTE algorithm had the highest F1 Score and MCC values among all machine learning algorithms. © 2025 Elsevier B.V., All rights reserved.Conference Object Optimal Fixed-Wing UAV Rendezvous Via LQR-Based Longitudinal Control(IEEE, 2025) Buyukekiz, Kadir Bulathan; Ergezer, HalitThis paper proposes an optimal control-based rendezvous strategy for fixed-wing Unmanned Aerial Vehicles (UAVs) using a Linear Quadratic Regulator (LQR). The goal is precisely tracking a moving target while maintaining flight stability and avoiding predefined restricted areas. The controller optimally adjusts UAVs flight parameters to minimize trajectory errors and enhance robustness against environmental disturbances. A penalty-based method is integrated to prevent UAVs from entering restricted areas while ensuring smooth trajectory adaptation. The proposed approach has been tested in MATLAB simulations under multiple scenarios, demonstrating its effectiveness in achieving stable and efficient rendezvous maneuvers. The results confirm that LQR-based control and adaptive penalty mechanisms offer a practical solution for fixed-wing UAV operations in constrained environments.Conference Object Formation Control of Fixed-Wing Uavs Using Mpc: Effect of Vehicle Speed(Ieee, 2024) Ozcelik, Ozge Kartal; Ergezer, HalitAs UAV technology has progressed, its applications have expanded across various sectors such as Surveillance, Military, Maintenance, and Delivery. Due to their cost-effectiveness and safety in operations, UAVs have gained rapid popularity in these domains. Scenarios demanding the coordinated flight of multiple UAVs have become prevalent, leading to various formation types and control strategies tailored to specific use cases. Among these control mechanisms, Model Predictive Control (MPC) has found application in UAV formation flight. This study focuses on the development and implementation of MPC for the formation flight of fixed-wing UAVs. Experiments were conducted utilizing a setup involving three UAVs, elucidating the functionality of MPC and examining the impact of variations in the speed parameter on MPC performance.