期刊论文

An, Jiyao

英文

IEEE ACCESS

2169-3536

2019

7

120581-120593

10.1109/ACCESS.2019.2920430

This work was supported in part by the National Key Research and Development Plan of China under Grant 2016YFB0200405, in part by the National Natural Science Foundation of China under Grant 61672217, Grant 61370097, and Grant 61602164, in part by the Natural Science Foundation of Hunan Province, China, under Grant 2018JJ2063, Grant 2018JJ3076, and Grant 2018JJ3023, and in part by the outstanding youth project of education department of Hunan Province, China, under Grant 15B044.

本校为其他机构

Accuracy is extensively considered a key issue for traffic big data prediction in a vehicular cyber-physical system (VCPS). Deep learning with super performance has been successfully applied to traffic prediction for feature learning. However, uncertain traffic big data pose a remarkable challenge on current deep learning models, which work in a vector space in a deterministic manner and fail to learn the features of uncertain traffic data. This study solves the problem of citywide traffic flow prediction to satisfy the accuracy requirement of ...