Deep learning for spatio-temporal data mining: A survey
With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …
A survey on embedding dynamic graphs
Embedding static graphs in low-dimensional vector spaces plays a key role in network
analytics and inference, supporting applications like node classification, link prediction, and …
analytics and inference, supporting applications like node classification, link prediction, and …
Deep learning on traffic prediction: Methods, analysis, and future directions
X Yin, G Wu, J Wei, Y Shen, H Qi… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Traffic prediction plays an essential role in intelligent transportation system. Accurate traffic
prediction can assist route planing, guide vehicle dispatching, and mitigate traffic …
prediction can assist route planing, guide vehicle dispatching, and mitigate traffic …
[HTML][HTML] Bike sharing usage prediction with deep learning: a survey
W Jiang - Neural Computing and Applications, 2022 - Springer
As a representative of shared mobility, bike sharing has become a green and convenient
way to travel in cities in recent years. Bike usage prediction becomes more important for …
way to travel in cities in recent years. Bike usage prediction becomes more important for …
Improving short-term bike sharing demand forecast through an irregular convolutional neural network
As an important task for the management of bike sharing systems, accurate forecast of travel
demand could facilitate dispatch and relocation of bicycles to improve user satisfaction. In …
demand could facilitate dispatch and relocation of bicycles to improve user satisfaction. In …
Artificial intelligence for social good: A survey
Artificial intelligence for social good (AI4SG) is a research theme that aims to use and
advance artificial intelligence to address societal issues and improve the well-being of the …
advance artificial intelligence to address societal issues and improve the well-being of the …
Deep spatio-temporal adaptive 3d convolutional neural networks for traffic flow prediction
Traffic flow prediction is the upstream problem of path planning, intelligent transportation
system, and other tasks. Many studies have been carried out on the traffic flow prediction of …
system, and other tasks. Many studies have been carried out on the traffic flow prediction of …
TAGCN: Station-level demand prediction for bike-sharing system via a temporal attention graph convolution network
W Zi, W Xiong, H Chen, L Chen - Information Sciences, 2021 - Elsevier
Nowadays, bike-sharing is available in many cities, solving the problem of the last mile, and
it is an environmental-friendly way to commute. However, there is a tidal phenomenon in the …
it is an environmental-friendly way to commute. However, there is a tidal phenomenon in the …
Spatio-temporal neural structural causal models for bike flow prediction
As a representative of public transportation, the fundamental issue of managing bike-sharing
systems is bike flow prediction. Recent methods overemphasize the spatio-temporal …
systems is bike flow prediction. Recent methods overemphasize the spatio-temporal …
A graph and attentive multi-path convolutional network for traffic prediction
Traffic prediction is an important and yet highly challenging problem due to the complexity
and constantly changing nature of traffic systems. To address the challenges, we propose a …
and constantly changing nature of traffic systems. To address the challenges, we propose a …