Handling Imbalanced Data for Real-Time Crash Prediction: Application of Boosting and Sampling Techniques-Reference-Cited by-同舟云学术

Handling Imbalanced Data for Real-Time Crash Prediction: Application of Boosting and Sampling Techniques

Published:2021-03 Issue:3 Volume:147 Page:04020165
ISSN:2473-2907
Container-title:Journal of Transportation Engineering, Part A: Systems
language:en
Short-container-title:J. Transp. Eng., Part A: Systems

Author:

Ariannezhad Amin¹^ORCID,Karimpour Abolfazl²^ORCID,Qin Xiao³,Wu Yao-Jan⁴^ORCID,Salmani Yasamin⁵^ORCID

Affiliation:

1. Research Assistant, Dept. of Civil and Architectural Engineering and Mechanics, Univ. of Arizona, Tucson, AZ 85721 (corresponding author). ORCID: .

2. Graduate Research Assistant, Dept. of Civil and Architectural Engineering and Mechanics, Univ. of Arizona, Tucson, AZ 85721. ORCID: .

3. Professor, Dept. of Civil and Environmental Engineering, Univ. of Wisconsin-Milwaukee, Milwaukee, WI 53211.

4. Associate Professor, Dept. of Civil and Architectural Engineering and Mechanics, Univ. of Arizona, Tucson, AZ 85721. ORCID: .

5. Assistant Professor of Project and Operations Management, Dept. of Management, College of Business, Bryant Univ., Smithfield, RI 02917. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/JTEPBS.0000499

Reference58 articles.

1. Assessing Safety on Dutch Freeways with Data from Infrastructure-Based Intelligent Transportation Systems

2. Predicting Freeway Crashes from Loop Detector Data by Matched Case-Control Logistic Regression

3. Calibrating a Real-Time Traffic Crash-Prediction Model Using Archived Weather and ITS Traffic Data

4. Assessment of interaction of crash occurrence, mountainous freeway geometry, real-time weather, and traffic data;Ahmed M.;Transp. Res. Rec.,2012

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