ATOM-S Conference 2024
- Operational Equipments for Wind and Waves Monitoring in Offshore Marine Industry
- Systems for Wind Monitoring on Black Sea Offshore
- Implementation and Evaluation of the Bearing Monitoring System in the Wind Sector using Vibration Sensors in the Context of Maintenance Engineering
- Multi-Processor Architecture Implemented for Indoor Air Quality Monitoring Devices
- Sensing System for Environmental Monitoring on the Black Sea Offshore Platform
- Waves induced wind impact on Floating Offshore Wind Turbines (FOWTs) in Black Sea
ECAI Conference 2024
ASMES 2024 Conference
- System for Monitoring Environmental Factors at the Galata Platform
DOORS Conference 2024
- Revolutionizing Offshore Wind Technology in the Black Sea: The BLOW project
- “Estimating Smart Grid Stability with Hybrid RNN+ LSTM Deep Learning Approach.” In 2024 12th International Conference on Smart Grid (icSmartGrid), pp. 738-741. IEEE, 2024.
- Analysis of SARIMA Models for Forecasting Electricity Demand. In 2024 12th International Conference on Smart Grid (icSmartGrid) (pp. 767-771). IEEE.
- “An overview of the wind statistics for Metocean Analytics on Galata platform”, Alternative Energy Sources, Materials & Technologies (AESMT), 2024.
- “Automation System for Wind Turbines.” In 2024 9th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE), pp. 1-6. IEEE, 2024.
- “Risk assessment using new environmental simulation tools”, In 2024 Lecture Notes on Multidisciplinary Industrial Engineering
- “METOCEAN SPECIFICATIONS FOR WIND DATA BASE ON THE BLACK SEA.” Journal of Marine Technology & Environment 2 (2023).
- “Considerations regarding qiling system for offshore wind turbines.” TransNav: International Journal on Marine Navigation and Safety of Sea Transportation 17 (2023).
- “Ensemble learning framework for DDoS detection in SDN-based SCADA systems.” Sensors 24, no. 1 (2023): 155.
- “Contributions to power Grid system analysis based on clustering techniques.” Sensors 23, no. 4 (2023): 1895.
- “Integrating Machine Learning and MLOps for Wind Energy Forecasting: A Comparative Analysis and Optimization Study on Türkiye’s Wind Data.” Applied Sciences 14, no. 9 (2024): 3725.
- “Multi-stage learning framework using convolutional neural network and decision tree-based classification for detection of DDoS pandemic attacks in SDN-based SCADA systems.” Sensors 24, no. 3 (2024): 1040.
- “High-Performance Techniques and Technologies for Monitoring and Controlling Environmental Factors.” Hidraulica 1 (2024).
- “A review of the harvesting methods for offshore renewable energy-advances and challenges.” Journal of Marine Technology & Environment 2 (2024).
- “Unveiling the Wind Energy Future of Türkiye with Policies Technologies and Potential.” Heliyon (2025).