Traffic Flow Prediction and program codes

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) http://pems.doc.ca.gov; and Fremont Bridge Bicycle Counter (FBBC), https://data.seattle.gov.For more details, please refer to our paper entitled "Wide-Attention and Deep-Composite Model for Traffic Flow Prediction in Transportation Cyber-Physical Systems", accepted to appear in IEEE Transactions on Industrial Informatics and githubhttps://github.com/zhoujunhao/wadc.本数据集主要包含两部分内容：1）宽注意力与深度模型（Wide-Attention and Deep model, WADC）的源代码；2）用于评估所提模型性能的数据集。所用数据集取自加州交通局性能测量系统（Caltrans Performance Measurement System, CPeMS，网址：http://pems.doc.ca.gov）与弗里蒙特大桥自行车计数系统（Fremont Bridge Bicycle Counter, FBBC，网址：https://data.seattle.gov）。如需了解更多细节，请参阅我们已被接收并将发表于《IEEE工业信息学汇刊》的论文《面向交通信息物理系统的宽注意力与深度复合交通流预测模型》，以及项目GitHub仓库https://github.com/zhoujunhao/wadc。