Energy Consumption
Energy consumption research focuses on understanding and optimizing energy use across various sectors, from individual households and smart grids to large-scale AI systems and data centers. Current research emphasizes developing energy-efficient machine learning models (e.g., using transformers, convolutional neural networks, and recurrent neural networks) and employing techniques like federated learning to improve privacy while training models on distributed data. This work is crucial for mitigating the environmental impact of increasing energy demands and for improving the efficiency and sustainability of numerous technological applications.
Papers
Deep Learning for Forecasting the Energy Consumption in Public Buildings
Viorica Rozina Chifu, Cristina Bianca Pop, Emil St. Chifu, Horatiu Barleanu
Forecasting the Short-Term Energy Consumption Using Random Forests and Gradient Boosting
Cristina Bianca Pop, Viorica Rozina Chifu, Corina Cordea, Emil Stefan Chifu, Octav Barsan