Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting

H Peng, H Wang, B Du, MZA Bhuiyan, H Ma, J Liu… - Information …, 2020 - Elsevier
Accurate and real-time traffic passenger flows forecasting at transportation hubs, such as
subway/bus stations, is a practical application and of great significance for urban traffic …

Exploiting blockchain data to detect smart ponzi schemes on ethereum

W Chen, Z Zheng, ECH Ngai, P Zheng, Y Zhou - IEEE Access, 2019 - ieeexplore.ieee.org
Blockchain technology becomes increasingly popular. It also attracts scams, for example, a
Ponzi scheme, a classic fraud, has been found making a notable amount of money on …

Spatio-temporal analysis of passenger travel patterns in massive smart card data

J Zhao, Q Qu, F Zhang, C Xu… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Metro systems have become one of the most important public transit services in cities. It is
important to understand individual metro passengers' spatio-temporal travel patterns. More …

Federated anomaly analytics for local model poisoning attack

S Shi, C Hu, D Wang, Y Zhu… - IEEE Journal on Selected …, 2021 - ieeexplore.ieee.org
The local model poisoning attack is an attack to manipulate the shared local models during
the process of distributed learning. Existing defense methods are passive in the sense that …

Big data and emergency management: concepts, methodologies, and applications

X Song, H Zhang, R Akerkar, H Huang… - … Transactions on Big …, 2020 - ieeexplore.ieee.org
Recent decades have seen a significant increase in the frequency, intensity, and impact of
natural disasters and other emergencies, forcing the governments around the world to make …

[PDF][PDF] Neural Network based Continuous Conditional Random Field for Fine-grained Crime Prediction.

F Yi, Z Yu, F Zhuang, B Guo - IJCAI, 2019 - ijcai.org
Crime prediction has always been a crucial issue for public safety, and recent works have
shown the effectiveness of taking spatial correlation, such as region similarity or interaction …

Online deep ensemble learning for predicting citywide human mobility

Z Fan, X Song, T **a, R Jiang, R Shibasaki… - Proceedings of the …, 2018 - dl.acm.org
Predicting citywide human mobility is critical to an effective management and regulation of
city governance, especially during a rare event (eg large event such as New Year's …