10 citations · 26 across the 15 of their papers we have counts for
7 papers · 1 filter
Transformer-based Drum-level Prediction in a Boiler Plant with Delayed Relations among Multivariates
Gang Su, Sun Yang, Zhishuai Li
The steam drum water level is a critical parameter that directly impacts the safety and efficiency of power plant operations. However, predicting the drum water level in boilers is…
TraffiDent: A Dataset for Understanding the Interplay Between Traffic Dynamics and Incidents
Xiaochuan Gou, Ziyue Li, Tian Lan +6
Long-separated research has been conducted on two highly correlated tracks: traffic and incidents. Traffic track witnesses complicating deep learning models, e.g., to push the pred…
Non-Neighbors Also Matter to Kriging: A New Contrastive-Prototypical Learning
Zhishuai Li, Yunhao Nie, Ziyue Li +3
Kriging aims at estimating the attributes of unsampled geo-locations from observations in the spatial vicinity or physical connections, which helps mitigate skewed monitoring cause…
Spatial-Temporal Large Language Model for Traffic Prediction
Chenxi Liu, Sun Yang, Qianxiong Xu +4
Traffic prediction, an essential component for intelligent transportation systems, endeavours to use historical data to foresee future traffic features at specific locations. Altho…
A Critical Perceptual Pre-trained Model for Complex Trajectory Recovery
Dedong Li, Ziyue Li, Zhishuai Li +5
The trajectory on the road traffic is commonly collected at a low sampling rate, and trajectory recovery aims to recover a complete and continuous trajectory from the sparse and di…
KITS: Inductive Spatio-Temporal Kriging with Increment Training Strategy
Qianxiong Xu, Cheng Long, Ziyue Li +3
Sensors are commonly deployed to perceive the environment. However, due to the high cost, sensors are usually sparsely deployed. Kriging is the tailored task to infer the unobserve…
Dynamic Causal Graph Convolutional Network for Traffic Prediction
Junpeng Lin, Ziyue Li, Zhishuai Li +3
Modeling complex spatiotemporal dependencies in correlated traffic series is essential for traffic prediction. While recent works have shown improved prediction performance by usin…