Convolutional neural networks; Long Short-Term Memory; Attention Mechanism; Traffic Flow Prediction; Transportation Cyber-Physical Systems

Many of the publicly available electrocardiogram (ECG) databases either have a low number of people in the database, each with longer recordings, or have more people, each with shorter recordings. As a result, attempting to split a single database into training, testing, and, optionally, validation datasets is challenging. Some models seem to do well with larger training sets, but that leaves only a small set of data for testing. Moreover, if the ECG is segmented by heartbeat, the data are further limited by the number of heartbeats in the recording.


This dataset mainly consists 1) source codes of wide-attention and deep model (WADC); 2) datasets to evaluate the performance of the proposed model. Datasets are obtained from the Caltrans Performance Measurement System (CPeMS); and Fremont Bridge Bicycle Counter (FBBC),