Estimating Construction Work Zones Capacity Using Deep Neural Network-Reference-Cited by-同舟云学术

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Estimating Construction Work Zones Capacity Using Deep Neural Network

Published:2022-03-07 Issue: Volume: Page:
ISSN:
Container-title:Construction Research Congress 2022
language:
Short-container-title:

Author:

Mashhadi Ali Hassandokht¹²²,Markovic Nikola¹²²,Rashidi Abbas¹²²

Affiliation:

1. Ph.D. Student of Construction Engineering, Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City. ORCID: https://orcid.org/0000-0002-7792-4645.

2. Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784483961.011

Reference18 articles.

1. Neuro-Fuzzy Logic Model for Freeway Work Zone Capacity Estimation

2. Arguea, D. F. 2006. Simulation-based approach to estimate the capacity of a temporary freeway work zone lane closure.

3. Estimating uncertainty of work zone capacity using neural network models;Bian Z.;Transportation research record,2019

4. TAB Bid Irregularity: Data-Driven Model and Its Application

5. Highway Asset and Pavement Condition Management using Mobile Photogrammetry;Farhadmanesh M.;Transportation Research Record,2021

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