A Comparative Study of Three Multivariate Short-Term Freeway Traffic Flow Forecasting Methods With Missing Data-Reference-Cited by-同舟云学术

A Comparative Study of Three Multivariate Short-Term Freeway Traffic Flow Forecasting Methods With Missing Data

Published:2016-04-22 Issue:3 Volume:20 Page:205-218
ISSN:1547-2450
Container-title:Journal of Intelligent Transportation Systems
language:en
Short-container-title:Journal of Intelligent Transportation Systems

Author:

Zhang Yanru¹,Zhang Yunlong²

Affiliation:

1. Department of Civil & Environmental Engineering, University of Maryland, College Park, Maryland, USA

2. Zachry Department of Civil Engineering, Texas A&M University, College Station, Texas, USA

Publisher

Informa UK Limited

Subject

Applied Mathematics,Computer Science Applications,Aerospace Engineering,Automotive Engineering,Information Systems,Software,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15472450.2016.1147813

Reference29 articles.

1. A generalized regression neural network and its application for leaf wetness prediction to forecast plant disease

2. A review of neural networks applied to transport

3. Data Collection Time Intervals for Stochastic Short-Term Traffic Flow Forecasting

4. Forecasting Traffic Flow Conditions in an Urban Network: Comparison of Multivariate and Univariate Approaches

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