Adaptive Real-Time Prediction Model for Short-Term Traffic Flow Uncertainty-Reference-Cited by-同舟云学术

Adaptive Real-Time Prediction Model for Short-Term Traffic Flow Uncertainty

Published:2020-08 Issue:8 Volume:146 Page:04020075
ISSN:2473-2907
Container-title:Journal of Transportation Engineering, Part A: Systems
language:en
Short-container-title:J. Transp. Eng., Part A: Systems

Author:

Li Wenhao¹,Ji Yanjie²,Wang Tao³

Affiliation:

1. Ph.D. Candidate, School of Transportation, Southeast Univ., 79 Suyuan Ave., Jiangning District, Nanjing, Jiangsu 211189, China.

2. Associate Professor, School of Transportation, Southeast Univ., 79 Suyuan Ave., Jiangning District, Nanjing, Jiangsu 211189, China (corresponding author).

3. Associate Professor, School of Architecture and Transportation Engineering, Guilin Univ. of Electronic Technology, No. 1 Jinji Rd., Guilin, Guangxi 541004, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/JTEPBS.0000396

Reference32 articles.

1. A hybrid model using logistic regression and wavelet transformation to detect traffic incidents

2. Intelligent Transportation Systems

3. Extracting qualitative dynamics from experimental data

4. Multiple sources and multiple measures based traffic flow prediction using the chaos theory and support vector regression method;Cheng A.;Physica A,2017

5. Chaos theory and transportation systems: Instructive example;Frazier C.;Transp. Res. Rec.,2004

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Explainable Stacking-Based Learning Model for Traffic Forecasting;Journal of Transportation Engineering, Part A: Systems;2024-04

2. A deep learning and ensemble learning based architecture for metro passenger flow forecast;IET Intelligent Transport Systems;2022-09-14

3. Hybrid Deep Spatio-Temporal Models for Traffic Flow Prediction on Holidays and Under Adverse Weather;IEEE Access;2021

4. Airport Arrival Flow Prediction considering Meteorological Factors Based on Deep-Learning Methods;Complexity;2020-10-26