TÜBİTAK 1001: AI-Based Forecasting Models for Energy, Finance, and Digital Marketing

The project entitled “Advanced Time Series Forecasting and Uncertainty Analysis for Energy, Finance, and Digital Marketing Applications Using Deep Learning Models and an Adaptive Global Kalman Filter,” coordinated by Prof. Dr. Selami Beyhan from the Department of Artificial Intelligence and Data Engineering, has been selected for funding under the TÜBİTAK ARDEB 1001 Program. The project focuses on developing innovative artificial intelligence-based time series forecasting approaches capable of performing uncertainty analysis on complex datasets in the fields of energy, finance, and digital marketing. By integrating deep learning techniques with adaptive Kalman filtering methods, the research aims to strengthen decision-support processes and enhance uncertainty management capabilities across multiple sectors through advanced analytics and predictive modeling.