Browsing by Author "Filiz, G."

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    Tracking Step Counts in Adolescents With Juvenile Idiopathic Arthritis and Familial Mediterranean Fever: a 3-Month M-Health Monitoring Study Using Smartwatches
    (Elsevier, 2025) Albayrak, A.; Arman, N.; Yekdaneh, A.; Donmez, I.; Acikgoz, Y.; Filiz, G.; Ayaz, N. Aktay; Cakar, T.
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    Citation - Scopus: 1
    Artificial Intelligence Driven Multivariate Time Series Analysis of Network Traffic Prediction
    (Institute of Electrical and Electronics Engineers Inc., 2024) Filiz, G.; Yıldız, A.; Kara, E.; Altıntaş, S.; Çakar, T.
    The primary objective of this research is to employ artificial intelligence, machine learning, and neural networks in order to construct a network traffic prediction model. The analysis of network traffic data obtained from a digital media and entertainment provider operating in Turkey is conducted through the application of multivariate time-series analysis techniques in order to get insights into the temporal patterns and trends. In model development, Vector Autoregression (VAR), Vector Error Correction Model (VECM), Long-Short Term Memory (LSTM), and Gated Recurrent Unit (GRU) algorithms have been utilized. LSTM and GRU models have performed better with low Mean Absolute Percentage Error (MAPE) and high R-squared Score (R2). LSTM model has reached 0.98 R2 and 8.95% MAPE. These results indicate that the models can be utilized in network management optimization as resource allocation, congestion detection, anomaly detection, and quality of service. © 2024 IEEE.