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

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...

Full description

Bibliographic Details
Main Authors: Zhihan Cui, Boyu Huang, Haowen Dou, Guanru Tan, Shiqiang Zheng, Teng Zhou
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:IET Intelligent Transport Systems
Subjects:
Optimisation techniques
Traffic engineering computing
Other topics in statistics
Combinatorial mathematics
Machine learning (artificial intelligence)
Neural nets
Online Access:https://doi.org/10.1049/itr2.12127

Internet

https://doi.org/10.1049/itr2.12127

Similar Items