1 code implementation • Applied Energy 2023 • Mert Nakıp, Onur Çopur, Emrah Biyik, Cüneyt Güzeliş
Smart home energy management systems help the distribution grid operate more efficiently and reliably, and enable effective penetration of distributed renewable energy sources.
no code implementations • 22 Jun 2023 • Mert Nakıp, Erol Gelenbe
This paper proposes a novel Self-Supervised Intrusion Detection (SSID) framework, which enables a fully online Deep Learning (DL) based Intrusion Detection System (IDS) that requires no human intervention or prior off-line learning.
no code implementations • 22 Jun 2023 • Mert Nakıp, Baran Can Gül, Erol Gelenbe
Cyberattacks are increasingly threatening networked systems, often with the emergence of new types of unknown (zero-day) attacks and the rise of vulnerable devices.
no code implementations • 23 Mar 2023 • Erol Gelenbe, Mert Nakıp
Thus this work introduces a collective Botnet attack classification technique that operates on traffic from an n-node IP network with a novel Associated Random Neural Network (ARNN) that identifies the nodes which are compromised.
1 code implementation • 8 Apr 2022 • Onur Copur, Mert Nakıp, Simone Scardapane, Jürgen Slowack
Recognition of user interaction, in particular engagement detection, became highly crucial for online working and learning environments, especially during the COVID-19 outbreak.
1 code implementation • IEEE Access 2021 • Mert Nakıp, Cüneyt Güzeliş, Osman Yildiz
We propose a Recurrent Trend Predictive Neural Network (rTPNN) for multi-sensor fire detection based on the trend as well as level prediction and fusion of sensor readings.
Ranked #1 on Fire Detection on NIST Report of Test FR 4016
no code implementations • 6 Nov 2020 • Mert Nakıp, Onur Çopur, Cüneyt Güzeliş
The paper shows that simple linear regression models provide high prediction accuracy values reliably but only for a 2-weeks period and that relatively complex machine learning models, which have the potential of learning long term predictions with low errors, cannot achieve to obtain good predictions with possessing a high generalization ability.