A Heterogeneous Ensemble Approach for Travel Time Prediction Using Hybridized Feature Spaces and Support Vector Regression

A Heterogeneous Ensemble Approach for Travel Time Prediction Using Hybridized Feature Spaces and Support Vector Regression

Travel time prediction is essential to intelligent transportation systems directly affecting smart cities and autonomous vehicles. Accurately predicting traffic based on heterogeneous factors is highly beneficial but remains a challenging problem. The literature shows significant performance improve...

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Bibliographic Details
Main Authors: Jawad-ur-Rehman Chughtai, Irfan ul Haq, Saif ul Islam, Abdullah Gani
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Sensors
Subjects:
intelligent transportation systems
travel time prediction
hybridized feature space
heterogeneous ensemble learning
Online Access:https://www.mdpi.com/1424-8220/22/24/9735

Internet

https://www.mdpi.com/1424-8220/22/24/9735

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