3 papers
cs.LG2026
A Graph Prompt Fine-Tuning Method for WSN Spatio-Temporal Correlation Anomaly Detection
Miao Ye, Jing Cui, Yuan huang +3
Anomaly detection of multi-temporal modal data in Wireless Sensor Network (WSN) can provide an important guarantee for reliable network operation. Existing anomaly detection method…
eess.SP2025
Spatiotemporal Prediction of Electric Vehicle Charging Load Based on Large Language Models
Hang Fan, Mingxuan Li, Jingshi Cui +3
The rapid growth of EVs and the subsequent increase in charging demand pose significant challenges for load grid scheduling and the operation of EV charging stations. Effectively h…
cs.LG2025
A New Spatiotemporal Correlation Anomaly Detection Method that Integrates Contrastive Learning and Few-Shot Learning in Wireless Sensor Networks
Miao Ye, Suxiao Wang, Jiaguang Han +5
Detecting anomalies in the data collected by WSNs can provide crucial evidence for assessing the reliability and stability of WSNs. Existing methods for WSN anomaly detection often…