Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/82275
PIRA download icon_1.1View/Download Full Text
Title: A sample-rebalanced outlier-rejected k-nearest neighbor regression model for short-term traffic flow forecasting
Authors: Cai, LR
Yu, YD
Zhang, SY
Song, Y 
Xiong, Z
Zhou, T 
Issue Date: 2020
Source: IEEE access, 2020, v. 8, p. 22686-22696
Abstract: Short-term traffic flow forecasting is a fundamental and challenging task due to the stochastic dynamics of the traffic flow, which is often imbalanced and noisy. This paper presents a sample-rebalanced and outlier-rejected k-nearest neighbor regression model for short-term traffic flow forecasting. In this model, we adopt a new metric for the evolutionary traffic flow patterns, and reconstruct balanced training sets by relative transformation to tackle the imbalance issue. Then, we design a hybrid model that considers both local and global information to address the limited size of the training samples. We employ four real-world benchmark datasets often used in such tasks to evaluate our model. Experimental results show that our model outperforms state-of-the-art parametric and non-parametric models.
Keywords: Intelligent transportation systems
Road transportation
Time series analysis
Stochastic processes
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE access 
EISSN: 2169-3536
DOI: 10.1109/ACCESS.2020.2970250
Rights: This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/
The following publication L. Cai, Y. Yu, S. Zhang, Y. Song, Z. Xiong and T. Zhou, "A Sample-Rebalanced Outlier-Rejected $k$ -Nearest Neighbor Regression Model for Short-Term Traffic Flow Forecasting," in IEEE Access, vol. 8, pp. 22686-22696, 2020 is available at https://dx.doi.org/10.1109/ACCESS.2020.2970250
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Cai_Sample-Rebalanced_Outlier-Rejected_K-Nearest.pdf2.25 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

26
Citations as of May 22, 2022

Downloads

38
Citations as of May 22, 2022

SCOPUSTM   
Citations

28
Citations as of May 20, 2022

WEB OF SCIENCETM
Citations

18
Citations as of May 19, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.