Freeway Travel Time Prediction Based on Ensemble Learning Approaches-Reference-Cited by-同舟云学术

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Freeway Travel Time Prediction Based on Ensemble Learning Approaches

Published:2023-06-13 Issue: Volume: Page:
ISSN:
Container-title:International Conference on Transportation and Development 2023
language:
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Author:

Chen Zhen¹²,Fan Wei (David)¹²

Affiliation:

1. Traffic Engineer, Parsons Corporation, Atlanta, GA; formerly, INES Ph.D. Research Assistant, USDOT Center for Advanced Multimodal Mobility Solutions and Education, Univ. of North Carolina at Charlotte, Charlotte, NC.

2. Director and Professor, USDOT Center for Advanced Multimodal Mobility Solutions and Education, Dept. of Civil and Environmental Engineering, Univ. of North Carolina at Charlotte, Charlotte, NC.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784484876.036

Reference32 articles.

1. Intersection Traffic Prediction Using Decision Tree Models

2. A comparison of decision tree ensemble creation techniques;Banfield R. E.;IEEE Transactions on Pattern Analysis and Machine Intelligence,2006

3. Bagging predictors

4. Exploring travel time distribution and variability patterns using probe vehicle data: case study in Beijing;Chen P.;J. of Adv.Transportation,2018

5. Chen, T., and Guestrin, C. (2016). “XGboost: a scalable tree boosting system.” In Proc. of the 22nd ACM Sigkdd Internatl. Conf. on Knowledge Discovery and Data Mining. California, USA.

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