Urban mobility analytics: A deep spatial–temporal product neural network for traveler attributes inference

C Li, L Bai, W Liu, L Yao, ST Waller - Transportation Research Part C …, 2021 - Elsevier
This study examines the potential of using smart card data in public transit systems to infer
attributes of travelers, thereby facilitating a more user-centered public transport service …

[책][B] Unsupervised Multivariate Time Series Anomaly Detection via Transformer-based models and Time Series Encoding

T Duan - 2021 - search.proquest.com
This thesis has investigated the anomaly detection problem on multivariate time series. In
particular, we have studied two different directions: the point-based approach and the range …

Urban Mobility Analytics: Understanding, Inference and Forecasting

C Li - 2022 - unsworks.unsw.edu.au
Transport systems are the backbones of social and economic activities, which promote
industry development and accelerate the process of urbanization. However, the …

Deep Spatial-Temporal Learning in the Correlated Time Series

L Bai - 2021 - unsworks.unsw.edu.au
The fast evolution of mobile internet and remote sensing technologies has facilitated the
generation and collection of numerous time-series data from the real-world systems, which …