An ensemble machine learning‐based modeling framework for analysis of traffic crash frequency-Reference-Cited by-同舟云学术

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An ensemble machine learning‐based modeling framework for analysis of traffic crash frequency

Published:2019-07-31 Issue:3 Volume:35 Page:258-276
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer-Aided Civil and Infrastructure Engineering

Author:

Zhang Xiang¹,Waller S. Travis¹,Jiang Peng²

Affiliation:

1. Research Centre for Integrated Transport Innovation, School of Civil and Environmental EngineeringUniversity of New South Wales Sydney Australia

2. Geospatial Research Innovation and Development, Faculty of Built EnvironmentUniversity of New South Wales Sydney Australia

Funder

UNSW Digital Grid Futures Institute

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mice.12485

Reference96 articles.

1. Neural Networks in Civil Engineering: 1989–2000

2. Analysis of Road Crash Frequency with Spatial Models

3. A study of factors affecting highway accident rates using the random-parameters tobit model

4. Flagger Effects in Reducing the Likelihood of Rear-End Collisions for In-Platoon Vehicles in Work Zones

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