标题：A Data Grouping CNN Algorithm for Short-Term Traffic Flow Forecasting
作者：Yu, Donghai; Liu, Yang; Yu, Xiaohui
作者机构：[Yu, Donghai; Liu, Yang; Yu, Xiaohui] Shandong Univ, Sch Comp Sci & Technol, Jinan 250101, Peoples R China.; [Yu, Xiaohui] York Univ, Sch Informat T 更多
会议名称：18th Asia-Pacific Web Conference (APWeb)
会议日期：SEP 23-25, 2016
来源：Web Technologies and Applications, Pt I
关键词：Convolution Neural Network; Traffic flow forecasting; CBOW; Deep; learning
摘要：In this paper, a data grouping approach based on convolutional neural network (DGCNN) is proposed for forecasting urban short-term traffic flow. This approach includes the consideration of spatial relations between traffic locations, and utilizes such information to train a convolutional neural network for forecasting. There are three advantages of our approach: (1) the spatial relations of traffic flow are adopted; (2) high-quality features are extracted by CNN; and (3) the accuracy of forecasting short-term traffic flow is improved. To verify our model, extensive experiments are performed on a real data set, and the result shows that the model is more effective than other existing methods.