Predicting financial losses due to apartment construction accidents utilizing deep learning techniques

This study aims to generate a deep learning algorithm-based model for quantitative prediction of financial losses due to accidents occurring at apartment construction sites. Recently, the construction of apartment buildings is rapidly increasing to solve housing shortage caused by increasing urban d...

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Bibliographic Details
Published in:Scientific reports 2022-03, Vol.12 (1), p.5365-5365, Article 5365
Main Authors: Kim, Ji-Myong, Bae, Junseo, Park, Hyunsoung, Yum, Sang-Guk
Format: Article
Language:English
Subjects:
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639/166/986
Accidents
Accidents, Occupational
Algorithms
Climate change
Construction
Construction industry
Deep Learning
Housing
Humanities and Social Sciences
multidisciplinary
Prediction models
Project engineering
Project management
Republic of Korea
Risk reduction
Science
Science (multidisciplinary)
Severe weather
Weather
Workplace
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Summary:This study aims to generate a deep learning algorithm-based model for quantitative prediction of financial losses due to accidents occurring at apartment construction sites. Recently, the construction of apartment buildings is rapidly increasing to solve housing shortage caused by increasing urban density. However, high-rise and large-scale construction projects are increasing the frequency and severity of accidents occurring inside and outside of construction sites, leading to increases of financial losses. In particular, the increase in severe weather and the surge in abnormal weather events due to climate change are aggravating the risk of financial losses associated with accidents occurring at construction sites. Therefore, for sustainable and efficient management of construction projects, a loss prediction model that prevents and reduces the risk of financial loss is essential. This study collected and analyzed insurance claim payout data from a main insurance company in South Korea regarding accidents occurring inside and outside of construction sites. Deep learning algorithms were applied to develop predictive models reflecting scientific and recent technologies. Results and framework of this study provide critical guidance on financial loss management necessary for sustainable and efficacious construction project management. They can be used as a reference for various other construction project management studies.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-022-09453-w