This study examines regional disparities in the factors that affect participation in the Private Pension System (PPS) in Türkiye, focusing on sociodemographic characteristics, personality traits and behavior, and pension and financial literacy. The behavioral factors identified encompass...

Traffic congestion in urban centers not only hampers mobility but also significantly impacts economic activities and environmental sustainability. This study leverages advanced machine learning techniques to analyze and predict traffic jams, utilizing a detailed dataset of 9847 recorded accident...

Effective long-term energy forecasting is essential for efficient management of large institutions like university campuses, yet traditional forecasting methods frequently fall short in capturing complex consumption behaviors. To bridge this gap, this study introduces an advanced machine...

This study investigates the impact of competition on credit risk in the Turkish banking system, focusing on Islamic (participation) and conventional banking under the same regulatory conditions regarding credit risk. The credit risk model is trained using CatBoost, extreme gradient boosting...

Predicting water quality in a heterogeneous watershed is challenging because parameters and prediction accuracy vary with space. Therefore, spatially adaptive machine learning models were introduced for predicting water quality conditions in the Haraz and Babolroud watersheds, Iran. Initially,...