4 papers
Machine Learning for Depression Screening and Intervention: an Original Circadian Rhythm Score-based Methodology
Bin Wang, Shuo Lian, Yuanyuan Hou +5
Depression screening from large-scale behavioral data is challenged by fragmented circadian indicators, limited interpretability, and the lack of intervention-oriented analysis. Ex…
Unlocking air traffic flow prediction through microscopic aircraft-state modeling
Bin Wang, Anqi Liu, Jiangtao Zhao +8
Short-term air traffic flow prediction in terminal airspace is essential for proactive air traffic management. Existing approaches predominantly model traffic flow as aggregated ti…
From Time Series to State: Situation-Aware Modeling for Air Traffic Flow Prediction
Anqi Liu, Jiangtao Zhao, Guiyuan Jiang +3
Accurate air traffic prediction in the terminal airspace (TA) is pivotal for proactive air traffic management (ATM). However, existing data-driven approaches predominantly rely on…
Non-collective Calibrating Strategy for Time Series Forecasting
Bin Wang, Yongqi Han, Minbo Ma +4
Deep learning-based approaches have demonstrated significant advancements in time series forecasting. Despite these ongoing developments, the complex dynamics of time series make i…