GSA‐ELM: A hybrid learning model for short‐term traffic flow forecasting

Abstract Accurate and timely short‐term traffic flow forecasting is an essential component for intelligent traffic management systems. However, developing an effective and robust forecasting model is challenging due to the inherent randomness and nonlinear characteristic of the traffic flow. In this...

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Detalles Bibliográficos

Principais autores:	Zhihan Cui, Boyu Huang, Haowen Dou, Guanru Tan, Shiqiang Zheng, Teng Zhou
Formato:	Artigo
Idioma:	Inglês
Publicado:	Wiley 2022-01-01
Series:	IET Intelligent Transport Systems
Assuntos:	Optimisation techniques Traffic engineering computing Other topics in statistics Combinatorial mathematics Machine learning (artificial intelligence) Neural nets
Acceso en liña:	https://doi.org/10.1049/itr2.12127
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