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Highway Traffic Flow Prediction Model Construction Based on the Gray Theory and BP Neural Network
The short-term traffic flow prediction and modeling of highways are the core content and important foundation of highway management decision-making support systems. It is of great significance to improving the level of highway management. Based on the macrodynamic traffic flow model, this article es...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9296314/ https://www.ncbi.nlm.nih.gov/pubmed/35865497 http://dx.doi.org/10.1155/2022/1120491 |
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author | Jiang, Zaiyang |
author_facet | Jiang, Zaiyang |
author_sort | Jiang, Zaiyang |
collection | PubMed |
description | The short-term traffic flow prediction and modeling of highways are the core content and important foundation of highway management decision-making support systems. It is of great significance to improving the level of highway management. Based on the macrodynamic traffic flow model, this article establishes a method for establishing a highway traffic flow prediction model based on the BP neural network theory and gray theory. We collected and carry out modeling and prediction of highway traffic flow data near a certain station. It is learned from the prediction results that the traffic flow prediction model based on the BP neural network and gray theory has a high degree of reliability. |
format | Online Article Text |
id | pubmed-9296314 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-92963142022-07-20 Highway Traffic Flow Prediction Model Construction Based on the Gray Theory and BP Neural Network Jiang, Zaiyang Comput Intell Neurosci Research Article The short-term traffic flow prediction and modeling of highways are the core content and important foundation of highway management decision-making support systems. It is of great significance to improving the level of highway management. Based on the macrodynamic traffic flow model, this article establishes a method for establishing a highway traffic flow prediction model based on the BP neural network theory and gray theory. We collected and carry out modeling and prediction of highway traffic flow data near a certain station. It is learned from the prediction results that the traffic flow prediction model based on the BP neural network and gray theory has a high degree of reliability. Hindawi 2022-07-12 /pmc/articles/PMC9296314/ /pubmed/35865497 http://dx.doi.org/10.1155/2022/1120491 Text en Copyright © 2022 Zaiyang Jiang. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Jiang, Zaiyang Highway Traffic Flow Prediction Model Construction Based on the Gray Theory and BP Neural Network |
title | Highway Traffic Flow Prediction Model Construction Based on the Gray Theory and BP Neural Network |
title_full | Highway Traffic Flow Prediction Model Construction Based on the Gray Theory and BP Neural Network |
title_fullStr | Highway Traffic Flow Prediction Model Construction Based on the Gray Theory and BP Neural Network |
title_full_unstemmed | Highway Traffic Flow Prediction Model Construction Based on the Gray Theory and BP Neural Network |
title_short | Highway Traffic Flow Prediction Model Construction Based on the Gray Theory and BP Neural Network |
title_sort | highway traffic flow prediction model construction based on the gray theory and bp neural network |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9296314/ https://www.ncbi.nlm.nih.gov/pubmed/35865497 http://dx.doi.org/10.1155/2022/1120491 |
work_keys_str_mv | AT jiangzaiyang highwaytrafficflowpredictionmodelconstructionbasedonthegraytheoryandbpneuralnetwork |