Snowplow Truck Performance Assessment and Feature Importance Analysis Using Machine-Learning Techniques-Reference-Cited by-同舟云学术

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Snowplow Truck Performance Assessment and Feature Importance Analysis Using Machine-Learning Techniques

Published:2021-02 Issue:2 Volume:147 Page:04020160
ISSN:2473-2907
Container-title:Journal of Transportation Engineering, Part A: Systems
language:en
Short-container-title:J. Transp. Eng., Part A: Systems

Author:

Yi Zhiyan¹^ORCID,Liu Xiaoyue Cathy²^ORCID,Wei Ran³,Grubesic Tony H.⁴^ORCID

Affiliation:

1. Ph.D. Student, Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City, UT 84112. ORCID: .

2. Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City, UT 84112 (corresponding author). ORCID: .

3. Associate Professor, School of Public Policy, Univ. of California, Riverside, Riverside, CA 92521.

4. Professor, School of Information, Univ. of Texas at Austin, Austin, TX 78701. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/JTEPBS.0000486

Reference26 articles.

1. Performance Measures for Winter Operations

2. Predictive maintenance using tree-based classification techniques: A case of railway switches;Bukhsh Z. A.;Transp. Res. Part C: Emerging Technol.,2019

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1. Analysis of Effect of Crossing Pedestrians on Traffic Characteristics at Urban Midblock Sections Using Support Vector Regression;Recent Advances in Transportation Systems Engineering and Management;2022-11-11

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