The College of Computer Science and Information Technology at University of Basrah organized a scientific lecture entitled:
“Predicting Energy Consumption Using Deep Learning and the Long Short-Term Memory Neural Network (LSTM) Model.”
The lecture aimed to highlight the importance of using deep learning techniques in analyzing temporal data for accurate energy consumption prediction. This contributes to improving the management of electrical grids, reducing operational costs, and supporting future planning for smart energy systems.
The lecture, presented by researcher Mohammed Redha Abdul Rahman Khassir Hamza, included an explanation of the data collection and processing methodology, the mechanism for training and evaluating the LSTM model using various accuracy metrics, and the role of this model in handling complex temporal data and its applicability in different buildings and across multiple horizons.
