Identifying relevant factors about work accidents in the road transport sector and the deaths relation in this scenario
Workers’ health and safety are a major concern in society, since work accidents have a major impact on productivity and economy. In Brazil, the accidents are officially reported through Work Accident Communication and they are available to the public. Thus, this study analyzed a balanced dataset con...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universidad Nacional de Colombia
2023-03-01
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| Series: | Dyna |
| Subjects: | |
| Online Access: | https://revistas.unal.edu.co/index.php/dyna/article/view/105688 |
| _version_ | 1797838780289253376 |
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| author | Lucimara Ferreira da Silva Beatriz Lavezo dos Reis Liandra Dos Santos Jesus Gislaine Camila Lapasini Leal Edwin Vladimir Cardoza Galdamez |
| author_facet | Lucimara Ferreira da Silva Beatriz Lavezo dos Reis Liandra Dos Santos Jesus Gislaine Camila Lapasini Leal Edwin Vladimir Cardoza Galdamez |
| author_sort | Lucimara Ferreira da Silva |
| collection | DOAJ |
| description | Workers’ health and safety are a major concern in society, since work accidents have a major impact on productivity and economy. In Brazil, the accidents are officially reported through Work Accident Communication and they are available to the public. Thus, this study analyzed a balanced dataset containing 1,206 records of deaths caused by work accidents related to the transport sector. Its aim was analyzing how the deaths in the transport sector are related with the other work accident factors. To achieve this goal, twelve performance data mining techniques are compared, through five performance metrics, regarding the predictive capacity of the occurrence of deaths caused by work accidents. In this context, the XGBoost and Naïve Bayes algorithms showed the best predictive capacity. The explanatory analysis indicates that work accidents followed by death in road transport are predictable due to the severity of the injuries and vital parts of the body are affected.
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| first_indexed | 2024-04-09T15:47:28Z |
| format | Article |
| id | doaj.art-6b241b826f6448de8ca2670f231ae4e8 |
| institution | Directory Open Access Journal |
| issn | 0012-7353 2346-2183 |
| language | English |
| last_indexed | 2024-04-09T15:47:28Z |
| publishDate | 2023-03-01 |
| publisher | Universidad Nacional de Colombia |
| record_format | Article |
| series | Dyna |
| spelling | doaj.art-6b241b826f6448de8ca2670f231ae4e82023-04-26T18:48:48ZengUniversidad Nacional de ColombiaDyna0012-73532346-21832023-03-019022510.15446/dyna.v90n225.105688Identifying relevant factors about work accidents in the road transport sector and the deaths relation in this scenarioLucimara Ferreira da Silva0Beatriz Lavezo dos Reis1Liandra Dos Santos Jesus2Gislaine Camila Lapasini Leal3Edwin Vladimir Cardoza Galdamez4Universidade Estadual de Maringá. Maringá, Paraná, BrasilUniversidade Estadual de Maringá. Maringá, Paraná, BrasilUniversidade Estadual de Maringá. Maringá, Paraná, BrasilUniversidade Estadual de Maringá. Maringá, Paraná, BrasilUniversidade Estadual de Maringá. Maringá, Paraná, BrasilWorkers’ health and safety are a major concern in society, since work accidents have a major impact on productivity and economy. In Brazil, the accidents are officially reported through Work Accident Communication and they are available to the public. Thus, this study analyzed a balanced dataset containing 1,206 records of deaths caused by work accidents related to the transport sector. Its aim was analyzing how the deaths in the transport sector are related with the other work accident factors. To achieve this goal, twelve performance data mining techniques are compared, through five performance metrics, regarding the predictive capacity of the occurrence of deaths caused by work accidents. In this context, the XGBoost and Naïve Bayes algorithms showed the best predictive capacity. The explanatory analysis indicates that work accidents followed by death in road transport are predictable due to the severity of the injuries and vital parts of the body are affected. https://revistas.unal.edu.co/index.php/dyna/article/view/105688data mining; occupational safety and health; transport sector; work accidents |
| spellingShingle | Lucimara Ferreira da Silva Beatriz Lavezo dos Reis Liandra Dos Santos Jesus Gislaine Camila Lapasini Leal Edwin Vladimir Cardoza Galdamez Identifying relevant factors about work accidents in the road transport sector and the deaths relation in this scenario Dyna data mining; occupational safety and health; transport sector; work accidents |
| title | Identifying relevant factors about work accidents in the road transport sector and the deaths relation in this scenario |
| title_full | Identifying relevant factors about work accidents in the road transport sector and the deaths relation in this scenario |
| title_fullStr | Identifying relevant factors about work accidents in the road transport sector and the deaths relation in this scenario |
| title_full_unstemmed | Identifying relevant factors about work accidents in the road transport sector and the deaths relation in this scenario |
| title_short | Identifying relevant factors about work accidents in the road transport sector and the deaths relation in this scenario |
| title_sort | identifying relevant factors about work accidents in the road transport sector and the deaths relation in this scenario |
| topic | data mining; occupational safety and health; transport sector; work accidents |
| url | https://revistas.unal.edu.co/index.php/dyna/article/view/105688 |
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