Forecasting System

Forecasting systems aim to predict future states based on historical data and current conditions, with applications ranging from weather prediction to traffic management and human-robot interaction. Recent research emphasizes the use of machine learning, particularly neural networks (including graph neural networks and transformer architectures), to improve forecasting accuracy and efficiency across diverse domains. These advancements leverage techniques like hierarchical interpolation, data assimilation, and cost-aware prediction to address challenges such as long-horizon forecasting and the integration of heterogeneous data sources. Improved forecasting capabilities have significant implications for various sectors, enhancing safety, resource management, and decision-making.