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A lightweight model using frequency, trend and temporal attention for long sequence time-series prediction.

, , , and . Neural Comput. Appl., 35 (28): 21291-21307 (October 2023)

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Traffic flow prediction using multi-view graph convolution and masked attention mechanism., , , and . Comput. Commun., (2022)A Sparse Cross Attention-based Graph Convolution Network with Auxiliary Information Awareness for Traffic Flow Prediction., , , , , and . CoRR, (2023)Anomaly Detection Using Spatio-Temporal Correlation and Information Entropy in Wireless Sensor Networks., , and . iThings/GreenCom/CPSCom/SmartData/Cybermatics, page 121-128. IEEE, (2020)FedAGCN: A traffic flow prediction framework based on federated learning and Asynchronous Graph Convolutional Network., , , , and . Appl. Soft Comput., (May 2023)A hypergrid based adaptive learning method for detecting data faults in wireless sensor networks., , and . Inf. Sci., (2021)ADGCN: An Asynchronous Dilation Graph Convolutional Network for Traffic Flow Prediction., , , and . IEEE Internet Things J., 9 (5): 4001-4014 (2022)A Missing Type-Aware Adaptive Interpolation Framework for Sensor Data., , , and . IEEE Trans. Instrum. Meas., (2021)An intelligent scheduling framework for DNN task acceleration in heterogeneous edge networks., , , and . Comput. Commun., (2023)A lightweight model using frequency, trend and temporal attention for long sequence time-series prediction., , , and . Neural Comput. Appl., 35 (28): 21291-21307 (October 2023)