Modelo predictivo de riesgos laborales en el gobierno autónomo descentralizado de Pichincha
Occupational safety is governed as a concern in the Decentralized Autonomous Government of Pichincha due to the occupational risks due to the negative impact, due to the lack of safety and health culture at work. Data Science can be helpful in addressing this problem, as it provides researchers with...
Gorde:
| Egile nagusia: | |
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| Formatua: | masterThesis |
| Hizkuntza: | spa |
| Argitaratua: |
2024
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| Gaiak: | |
| Sarrera elektronikoa: | https://repositorio.uteq.edu.ec/handle/43000/7822 |
| Etiketak: |
Etiketa erantsi
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Etiketa erantsi | Gaia: | Occupational safety is governed as a concern in the Decentralized Autonomous Government of Pichincha due to the occupational risks due to the negative impact, due to the lack of safety and health culture at work. Data Science can be helpful in addressing this problem, as it provides researchers with advanced tools and analytical techniques to study both small and large data sets. Despite this concern about accidents, few analyses have been conducted so far to identify specific trends or patterns. Therefore, this project focuses on analyzing a database containing information on accidents that occurred in the Pichincha GAD during the period 2015-2023 with the main objective of analyzing accidents. To achieve this, machine learning algorithms and data science techniques were employed to identify patterns and trends in workplace accidents. A detailed categorization of the data was carried out in order to better understand the variable behavior. In addition, a predictive model was developed using a linear regression-based approach that shows a progressive decrease in the total number of recorded accidents. Likewise, after performing a predictive analysis for the year 2023, a high concordance between the predicted and actual results is observed, which supports the accuracy of the model used. |
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