Multi-Objective Optimization of Construction Worker Unsafe Behavior Inducement Prediction Model

Xiaolong Wang; Guangtai Zhang; Erhu Li; Yan Wang; Kai Zhang

doi:10.2991/978-94-6463-256-9_174

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Multi-Objective Optimization of Construction Worker Unsafe Behavior Inducement Prediction Model

Authors

Xiaolong Wang¹, Guangtai Zhang²^{, 2}^{, *}, Erhu Li³, Yan Wang⁴, Kai Zhang⁵

¹School of Business, Xinjiang University, Urumqi, China

²School of Civil Engineering and Architecture, Xinjiang University, Urumqi, China

³School of Business, Xinjiang University, Urumqi, China

⁴School of Economics and Trade, Xihua University, Chengdu, China

⁵School of Mechanical Engineering, Xihua University, Chengdu, China

^*Corresponding author. Email: zgtlxh@126.com

Corresponding Author

Guangtai Zhang

Available Online 9 October 2023.

DOI: 10.2991/978-94-6463-256-9_174 How to use a DOI?
Keywords: machine learning; unsafe behaviors among construction workers; multi-objective optimization model; modern construction industry; high-quality development
Abstract: The predictive model for the causative factors of unsafe behaviors among construction workers is optimized with a multi-objective approach, based on the analysis of 27 factors and the use of four machine learning algorithms (CART, RF, AdaBoost, and GBDT) and genetic algorithms. Through a three-dimensional analysis of importance, correlation strength, and influence, five factors, namely risk awareness, education and training, hidden danger investigation and control, supervision level, and planning and design level, were identified to have the most significant impact on unsafe behaviors. This study aims to support the high-quality development of modern construction industry by studying the causative factors of unsafe behaviors among construction workers.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)
Series: Advances in Economics, Business and Management Research
Publication Date: 9 October 2023
ISBN: 978-94-6463-256-9
ISSN: 2352-5428
DOI: 10.2991/978-94-6463-256-9_174 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Xiaolong Wang
AU  - Guangtai Zhang
AU  - Erhu Li
AU  - Yan Wang
AU  - Kai Zhang
PY  - 2023
DA  - 2023/10/09
TI  - Multi-Objective Optimization of Construction Worker Unsafe Behavior Inducement Prediction Model
BT  - Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)
PB  - Atlantis Press
SP  - 1710
EP  - 1717
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-256-9_174
DO  - 10.2991/978-94-6463-256-9_174
ID  - Wang2023
ER  -

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