Dynamic Spatiotemporal Causality Analysis for Network Traffic Flow Based on Transfer Entropy and Sliding Window Approach
With the rapid development of sensor and communication technologies, a large amount of spatiotemporal traffic data has been accumulated, presenting the characteristics of big data. The potential information and regularity of traffic state evolution can be extracted from the huge traffic flow time se...
Saved in:
Main Authors: | Senyan Yang, Lianju Ning, Xilong Cai, Mingyu Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
|
Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2021/6616800 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Encrypted traffic identification scheme based on sliding window and randomness features
by: LIU Jiachi, et al.
Published: (2024-08-01) -
A Multiscale Symbolic Dynamic Entropy Analysis of Traffic Flow
by: Zhanyou Cui, et al.
Published: (2022-01-01) -
Air Traffic Flow Prediction with Spatiotemporal Knowledge Distillation Network
by: Zhiqi Shen, et al.
Published: (2024-01-01) -
Spatiotemporal Traffic Flow Prediction with KNN and LSTM
by: Xianglong Luo, et al.
Published: (2019-01-01) -
IPv6 Dynamic Address Tunnel Model Based on the Sliding Address Window
by: Zichuan Ma, et al.
Published: (2015-10-01)