A better understanding of long-range temporal dependence of traffic flow time series

S Feng, X Wang, H Sun, Y Zhang, L Li - Physica A: Statistical Mechanics …, 2018 - Elsevier
Long-range temporal dependence is an important research perspective for modelling of
traffic flow time series. Various methods have been proposed to depict the long-range …

Kernel PCA for road traffic data non‐linear feature extraction

W Yong‐dong, X Dong‐wei, P Peng… - IET Intelligent …, 2019 - Wiley Online Library
Road traffic data bring great challenges for data processing and traffic‐state analysis. The
feature extraction is an effective way to make full use of road traffic data. Here, the authors …

Low-dimensional models for traffic data processing using graph fourier transform

NB Chindanur, P Sure - Computing in Science & Engineering, 2018 - ieeexplore.ieee.org
The reliability of services offered by intelligent transportation systems is attributed to the
accuracy and timely availability of road-network traffic information. However, in the present …

Representing and Inferring Massive Network Traffic Condition: A Case Study in Nashville, Tennessee

H Zhang, Y Gu, LD Han - Algorithms, 2023 - mdpi.com
Intelligent transportation systems (ITSs) usually require monitoring of massive road networks
and gathering traffic data at a high spatial and temporal resolution. This leads to the …

A Study on the Compression and Major Pattern Extraction Method of Origin-Destination Data with Principal Component Analysis

J Kim, S Tak, J Yoon, H Yeo - The Journal of The Korea Institute of …, 2020 - koreascience.kr
Origin-destination data have been collected and utilized for demand analysis and service
design in various fields such as public transportation and traffic operation. As the utilization …

Did Everybody Come?

C Day - Comput. Sci. Eng., 2018 - computer.org
PURPOSE: The IEEE Computer Society is the world's largest association of computing
professionals and is the leading provider of technical information in the field. MEMBERSHIP …