Author

Kadriye Filiz Balbal

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Open access Jul 2026

A hybrid FinBERT-LSTM framework for Bitcoin price forecasting using news sentiment and technical indicators

A hybrid forecasting framework that integrates sentiment analysis with deep learning to predict Bitcoin’s hourly and daily closing prices and empirical results demonstrate that sentiment-enhanced hybrid models consistently outperform models based solely on technical indicators across RMSE, MAE, MAPE, and R² metrics.

Meltem Kavaklı, Kadriye Filiz Balbal · Balıkesir Üniversitesi Fen B... · 0 citations

Open access Jul 2026

M5Boost: A Machine Learning Approach for Driving Range Estimation in Electric Vehicles Considering Battery-Related Factors

An M5Boost framework is proposed that successfully integrates an additive residual learning methodology with the model tree structure and significantly outperformed state-of-the-art models reported in the literature on the same dataset.

I. Kubilay, Kadriye Filiz Balbal, K. Birant et al. · Batteries · 0 citations