Hybrid Extreme Learning for Reliable Short-Term Traffic Flow Forecasting

Hybrid Extreme Learning for Reliable Short-Term Traffic Flow Forecasting

Reliable forecasting of short-term traffic flow is an essential component of modern intelligent transport systems. However, existing methods fail to deal with the non-linear nature of short-term traffic flow, often making the forecasting unreliable. Herein, we propose a reliable short-term traffic f...

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Bibliographic Details
Main Authors:	Huayuan Chen, Zhizhe Lin, Yamin Yao, Hai Xie, Youyi Song, Teng Zhou
Format:	Article
Language:	English
Published:	MDPI AG 2024-10-01
Series:	Mathematics
Subjects:	hybrid extreme learning non-linear representation artificial bee colony short-term traffic flow forecasting
Online Access:	https://www.mdpi.com/2227-7390/12/20/3303
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