Predicting Serious Injury and Fatality Exposure Using Machine Learning in Construction Projects-Reference-Cited by-同舟云学术

Predicting Serious Injury and Fatality Exposure Using Machine Learning in Construction Projects

Published:2024-03 Issue:3 Volume:150 Page:
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Oguz Erkal Elif Deniz¹^ORCID,Hallowell Matthew R.²,Ghriss Ayoub³,Bhandari Siddharth⁴

Affiliation:

1. Graduate Research Assistant, Dept. of Civil, Environmental, and Architectural Engineering, Univ. of Colorado Boulder, Boulder, CO 80309-0428 (corresponding author). ORCID: .

2. K. Stanton Lewis Professor of Construction Engineering and Executive Director of the Construction Safety Research Alliance, Dept. of Civil, Environmental and Architectural Engineering, Univ. of Colorado, 1111 Engineering Dr., UCB 428, Boulder, CO 80309-0428.

3. Graduate Research Assistant, Dept. of Computer Science, Univ. of Colorado Boulder, Boulder, CO 80309-0428.

4. Associate Director of Construction Safety Research Alliance, Research Faculty, Dept. of Civil, Environmental, and Architectural Engineering, Univ. of Colorado, 1111 Engineering Dr., UCB 428, Boulder, CO 80309-0428.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JCEMD4.COENG-13741

Reference72 articles.

1. Experimental field testing of a real-time construction hazard identification and transmission technique

2. Empirical measurement and improvement of hazard recognition skill

3. Precursors of Construction Fatalities. I: Iterative Experiment to Test the Predictive Validity of Human Judgment

4. Precursors of Construction Fatalities. II: Predictive Modeling and Empirical Validation

5. Critical Success Factors for Construction Safety: Review and Meta-Analysis of Safety Leading Indicators

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