Short-term traffic flow prediction based on BAS-VMD-CEEMDAN and IWOA-RF-Reference-Cited by-同舟云学术

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Short-term traffic flow prediction based on BAS-VMD-CEEMDAN and IWOA-RF

Published:2023-07-30 Issue: Volume: Page:447-451
ISSN:
Container-title:2023 11th International Conference on Information Systems and Computing Technology (ISCTech)
language:
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Author:

Tian Jia¹,Wang Deyong²,Fn Yanyun³,Zhao Xueyi²,Fang Jian²,Shi Wenxi²

Affiliation:

1. Xinjiang University,School of Information Science and Engineering,Urumqi,China,830017

2. Xinjiang Lianhaichuangzhi Information Technology Co., Ltd,Key Laboratory of Big Data of Xinjiang Social Security Risk Prevention and Control,Urumqi,China,830011

3. Beijing Academy of Science and Technology,Beijing,China,100035

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10438204/10438228/10438299.pdf?arnumber=10438299

Reference4 articles.

1. A Hybrid Model for Lane-Level Traffic Flow Forecasting Based on Complete Ensemble Empirical Mode Decomposition and Extreme Gradient Boosting

2. A new prediction method based on VMD-PRBF-ARMA-E model considering wind speed characteristic

3. CEEMDAN-IPSO-LSTM: A Novel Model for Short-Term Passenger Flow Prediction in Urban Rail Transit Systems

4. The Whale Optimization Algorithm

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