An Optimization Framework for Crash Count Data Models-Reference-Cited by-同舟云学术

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An Optimization Framework for Crash Count Data Models

Published:2023-09-24 Issue: Volume:3 Page:2529-2534
ISSN:
Container-title:2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
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Author:

Macias Paula¹,Ahern Zeke¹,Corry Paul²,Rabbani Wahi³,Paz Alexander¹

Affiliation:

1. School of Civil & Environment Engineering, Queensland University of Technology,Brisbane,QLD,Australia,4000

2. School of Mathematical Sciences, Queensland University of Technology,Brisbane,QLD,Australia,4000

3. Queensland Department of Transport and Main Roads,Brisbane,QLD,Australia,4000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10420842/10420843/10422299.pdf?arnumber=10422299

Reference35 articles.

1. Investigating the effect of modeling single-vehicle and multi-vehicle crashes separately on confidence intervals of Poisson–gamma models

2. Analytic methods in accident research: Methodological frontier and future directions

3. A preference learning framework for multiple criteria sorting with diverse additive value models and valued assignment examples

4. Specification of mixed logit models assisted by an optimization framework

5. Empirical Bayes method in the study of traffic safety via heterogeneous negative multinomial model

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