Air quality prediction with physics-informed dual neural odes in open systems
Air pollution significantly threatens human health and ecosystems, necessitating effective air
quality prediction to inform public policy. Traditional approaches are generally categorized …
quality prediction to inform public policy. Traditional approaches are generally categorized …
DSSRNN: Decomposition-Enhanced State-Space Recurrent Neural Network for Time-Series Analysis
A Mohammadshirazi, A Nosratifiroozsalari… - arXiv preprint arXiv …, 2024 - arxiv.org
Time series forecasting is a crucial yet challenging task in machine learning, requiring
domain-specific knowledge due to its wide-ranging applications. While recent Transformer …
domain-specific knowledge due to its wide-ranging applications. While recent Transformer …
Fusing Pre-existing Knowledge and Machine Learning for Enhanced Building Thermal Modeling and Control
L Di Natale - 2024 - infoscience.epfl.ch
Buildings play a pivotal role in the ongoing worldwide energy transition, accounting for 30%
of the global energy consumption. With traditional engineering solutions reaching their limits …
of the global energy consumption. With traditional engineering solutions reaching their limits …