Anomaly Detection Using Spatio-Temporal Correlation and Information Entropy in Wireless Sensor Networks. - Lingqiang Chen; Li Xu; Guanghui Li 001 (iThings/GreenCom/CPSCom/SmartData/Cybermatics, 2020)

A hypergrid based adaptive learning method for detecting data faults in wireless sensor networks. - Lingqiang Chen; Guanghui Li 001; Guangyan Huang (Inf. Sci., 2021)

A Missing Type-Aware Adaptive Interpolation Framework for Sensor Data. - Lingqiang Chen; Guanghui Li 001; Guangyan Huang; Pei Shi (IEEE Trans. Instrum. Meas., 2021)

Traffic flow prediction using multi-view graph convolution and masked attention mechanism. - Lingqiang Chen; Pei Shi; Guanghui Li 001; Tao Qi (Comput. Commun., 2022)

ADGCN: An Asynchronous Dilation Graph Convolutional Network for Traffic Flow Prediction. - Tao Qi; Guanghui Li 001; Lingqiang Chen; Yanming Xue (IEEE Internet Things J., 2022)

An intelligent scheduling framework for DNN task acceleration in heterogeneous edge networks. - Yiming Feng; Shihong Hu; Lingqiang Chen; Guanghui Li 001 (Comput. Commun., 2023)

A Sparse Cross Attention-based Graph Convolution Network with Auxiliary Information Awareness for Traffic Flow Prediction. - Lingqiang Chen; Qinglin Zhao; Guanghui Li 001; Mengchu Zhou; Chenglong Dai; Yiming Feng (CoRR, 2023)

FedAGCN: A traffic flow prediction framework based on federated learning and Asynchronous Graph Convolutional Network. - Tao Qi; Lingqiang Chen; Guanghui Li 001; Yijing Li; Chenshu Wang (Appl. Soft Comput., 2023)

A lightweight model using frequency, trend and temporal attention for long sequence time-series prediction. - Lingqiang Chen; Guanghui Li 001; Guangyan Huang; Qinglin Zhao (Neural Comput. Appl., 2023)

A Sparse Cross Attention-Based Graph Convolution Network With Auxiliary Information Awareness for Traffic Flow Prediction. - Lingqiang Chen; Qinglin Zhao; Guanghui Li 001; Mengchu Zhou; Chenglong Dai; Yiming Feng; Xiaowei Liu; Jinjiang Li (IEEE Trans. Intell. Transp. Syst., 2025)