A Study on Classifying Construction Disaster Cases in Report with CNN for Effective Management

Ha Young Kim, Ye Eun Jang, Hyun Bin Kang, June Seong Yi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study proposes an efficient management direction for Korean construction disaster cases from KOSHA (Korea Occupational Safety & Health Agency) through a text data classification model based on CNN Algorithm. Five classes were defined to classify construction accidents: fall, electric shock, flying object, collapse, and narrowness. After the initial test, the classification accuracy of fall disasters was relatively high, while other types were mainly classified as fall disasters. These results showed that (1) specific accident-causing behavior, (2) similar sentence structure, and (3) complex accidents corresponding to complex types affect the model accuracy. Two improvement experiments were then conducted: (1) reclassification, and (2) elimination of complex accidents. With complex accidents eliminated, the classification performance improved by 185.7%. This result indicated that the multicollinearity of complex accidents was solved during elimination. In conclusion, this study suggests the necessity to manage complex accidents independently while preparing a system to describe the situation of future accidents in detail.

Original languageEnglish
Title of host publicationConstruction Research Congress 2022
Subtitle of host publicationComputer Applications, Automation, and Data Analytics - Selected Papers from Construction Research Congress 2022
EditorsFarrokh Jazizadeh, Tripp Shealy, Michael J. Garvin
PublisherAmerican Society of Civil Engineers (ASCE)
Pages483-491
Number of pages9
ISBN (Electronic)9780784483961
DOIs
StatePublished - 2022
EventConstruction Research Congress 2022: Computer Applications, Automation, and Data Analytics, CRC 2022 - Arlington, United States
Duration: 9 Mar 202212 Mar 2022

Publication series

NameConstruction Research Congress 2022: Computer Applications, Automation, and Data Analytics - Selected Papers from Construction Research Congress 2022
Volume2-B

Conference

ConferenceConstruction Research Congress 2022: Computer Applications, Automation, and Data Analytics, CRC 2022
Country/TerritoryUnited States
CityArlington
Period9/03/2212/03/22

Bibliographical note

Funding Information:
This work is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 22ORPS-B158109-03).

Publisher Copyright:
© 2022 ASCE.

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