Publications (5)
Citywide Electric Vehicle Charging Demand Prediction Approach Considering Urban Region and Dynamic Influences
Haoxuan Kuang, Kunxiang Deng, Linlin You +1
Electric vehicle charging demand prediction is important for vacant charging pile recommendation and charging infrastructure planning, thus facilitating vehicle electrification and…
BetaWeb: Towards a Blockchain-enabled Trustworthy Agentic Web
Zihan Guo, Yuanjian Zhou, Chenyi Wang +3
The rapid development of large language models (LLMs) has significantly propelled the development of artificial intelligence (AI) agents, which are increasingly evolving into diver…
A physics-informed and attention-based graph learning approach for regional electric vehicle charging demand prediction
Haohao Qu, Haoxuan Kuang, Jun Li +1
Along with the proliferation of electric vehicles (EVs), optimizing the use of EV charging space can significantly alleviate the growing load on intelligent transportation systems.…
Federated Knowledge Transfer Fine-tuning Large Server Model with Resource-Constrained IoT Clients
Shaoyuan Chen, Linlin You, Rui Liu +2
The training of large models, involving fine-tuning, faces the scarcity of high-quality data. Compared to the solutions based on centralized data centers, updating large models in…
Coupled Attention Networks for Multivariate Time Series Anomaly Detection
Feng Xia, Xin Chen, Shuo Yu +3
Multivariate time series anomaly detection (MTAD) plays a vital role in a wide variety of real-world application domains. Over the past few years, MTAD has attracted rapidly increa…