A Hybrid Method of Traffic Congestion Prediction and Control-Reference-Cited by-同舟云学术

A Hybrid Method of Traffic Congestion Prediction and Control

Published:2023 Issue: Volume:11 Page:36471-36491
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zhang Tianrui¹^ORCID,Xu Jianan¹^ORCID,Cong Sirui¹,Qu Chuansheng¹,Zhao Weibo²

Affiliation:

1. School of Mechanical and Engineering, Shenyang University, Shenyang, China

2. School of International Education, Shenyang University, Shenyang, China

Funder

China Central Guiding Local Science and Technology Development Fund Project “Application Research on Intelligent Collaborative Design and Control of Major Equipment Based on Cloud Service”

Liaoning Provincial Natural Science Foundation Project “Research on Key Technologies of MRO Service for Complex Equipment Oriented to the Full Life Cycle”

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10098740.pdf?arnumber=10098740

Reference24 articles.

1. Construction of traffic state vector using mutual information for short-term traffic flow prediction

2. An adaptive approach: Smart traffic congestion control system

3. Short‐term traffic flow prediction using fuzzy information granulation approach under different time intervals

4. Smart cities: Fusion-based intelligent traffic congestion control system for vehicular networks using machine learning techniques

5. Short-Term Traffic Flow Prediction Based on Least Square Support Vector Machine with Hybrid Optimization Algorithm

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