Short-Term Prediction of Traffic State for a Rural Road Applying Ensemble Learning Process
Short-term prediction of traffic variables aims at providing information for travelers before commencing their trips. In this paper, machine learning methods consisting of long short-term memory (LSTM), random forest (RF), support vector machine (SVM), and K-nearest neighbors (KNN) are employed to p...
Saved in:
Main Authors: | Arash Rasaizadi, Seyedehsan Seyedabrishami, Mohammad Saniee Abadeh |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
|
Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2021/3334810 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Spatial-Temporal Analysis of Crash Severity: Multisource Data Fusion Approach
by: Amirhossein Taheri, et al.
Published: (2022-01-01) -
Credit Risk Prediction Using Fuzzy Immune Learning
by: Ehsan Kamalloo, et al.
Published: (2014-01-01) -
Multidimensional Scaling-Based Data Dimension Reduction Method for Application in Short-Term Traffic Flow Prediction for Urban Road Network
by: Yi Zhao, et al.
Published: (2018-01-01) -
Transformer-based short-term traffic forecasting model considering traffic spatiotemporal correlation
by: Ande Chang, et al.
Published: (2025-01-01) -
Applying Clustered KNN Algorithm for Short-Term Travel Speed Prediction and Reduced Speed Detection on Urban Arterial Road Work Zones
by: Hyun Su Park, et al.
Published: (2022-01-01)