A heterogeneous ensemble approach for travel time prediction using hybridized feature spaces and support vector regression

HIGHLIGHTS

• who: Jawad-ur-Rehman Chughtai et al. from the Department of Computer and Information (DCIS), Institute of Engineering and Applied Faculty of Computing and Informatics, University Malaysia Sabah, Labuan, Malaysia have published the Article: A Heterogeneous Ensemble Approach for Travel Time Prediction Using Hybridized Feature Spaces and Support Vector Regression, in the Journal: Sensors 2022, 22, 9735. of /2022/
• what: This approach consists of three stages-initially six state-of-theart deep learning models are applied to traffic data obtained from Then the feature and decision scores (outputs) of the model with the highest performance . . .
  

   

  

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