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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 4/2021

19.01.2021

Short‐Term High-Speed Traffic Flow Prediction Based on ARIMA-GARCH-M Model

verfasst von: Xianfu Lin, Yuzhang Huang

Erschienen in: Wireless Personal Communications | Ausgabe 4/2021

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Abstract

The traditional traffic flow prediction model acquired the poor characteristics of the traffic flow time series, which led to the low prediction accuracy. Therefore, the short-term high-speed traffic flow prediction based on arima-garch-m model was proposed. According to the urban traffic flow theory, ARIMA model and GARCH model are combined to obtain the corresponding fluctuation characteristics and realize the prediction of traffic flow. The experimental results show that the NRMSE and MAPE of the model in this paper are only 3.13 % and 8.76 %, respectively, with good prediction accuracy and better stability and accuracy than the other two models, proving that the model has good performance and can meet the needs of practical application.
Vorheriger Artikel An Enhanced Green Cloud Based Queue Management (GCQM) System to Optimize Energy Consumption in Mobile Edge Computing
Nächster Artikel Method for Overflow Attack Defense of SDN Network Flow Table Based on Stochastic Differential Equation

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Metadaten
Titel
Short‐Term High-Speed Traffic Flow Prediction Based on ARIMA-GARCH-M Model
verfasst von
Xianfu Lin
Yuzhang Huang
Publikationsdatum
19.01.2021
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 4/2021
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-021-08085-z

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