Developing a National Data-Driven Construction Safety Management Framework with Interpretable Fatal Accident Prediction-Reference-Cited by-同舟云学术

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Developing a National Data-Driven Construction Safety Management Framework with Interpretable Fatal Accident Prediction

Published:2023-04 Issue:4 Volume:149 Page:
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Koc Kerim¹^ORCID,Ekmekcioğlu Ömer²^ORCID,Gurgun Asli Pelin³^ORCID

Affiliation:

1. Research Assistant, Dept. of Civil Engineering, Yildiz Technical Univ., Esenler, Istanbul 34220, Turkey (corresponding author). ORCID: .

2. Research Assistant, Dept. of Civil Engineering, Istanbul Technical Univ., Maslak, Istanbul 34469, Turkey. ORCID: .

3. Associate Professor, Dept. of Civil Engineering, Yildiz Technical Univ. Esenler, Istanbul 34220, Turkey. ORCID: .

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-12848

Reference131 articles.

1. Deep Learning Models for Health and Safety Risk Prediction in Power Infrastructure Projects

2. Alahassa N. K.-A. 2021. “State-of-the-art multivariate regression with a general N k hidden multi-layer feed forward neural network model.” In Proc. 2021 Int. Conf. on Artificial Intelligence and Computer Science Technology (ICAICST) 31–36. New York: IEEE.

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

4. Assessment of accident severity in the construction industry using the Bayesian theorem

5. Pareto Front Particle Swarm Optimizer for Discrete Time-Cost Trade-Off Problem

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