Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 1 de 1
Filter
Add more filters











Database
Language
Publication year range
1.
Sci Rep ; 12(1): 22084, 2022 12 21.
Article in English | MEDLINE | ID: mdl-36543811

ABSTRACT

The main objective of this study is to model the concentration of ozone in the winter season on air quality through machine learning algorithms, detecting its impact on population health. The study area involves four monitoring stations: Ate, San Borja, Santa Anita and Campo de Marte, all located in Metropolitan Lima during the years 2017, 2018 and 2019. Exploratory, correlational and predictive approaches are presented. The exploratory results showed that ATE is the station with the highest prevalence of ozone pollution. Likewise, in an hourly scale analysis, the pollution peaks were reported at 00:00 and 14:00. Finally, the machine learning models that showed the best predictive capacity for adjusting the ozone concentration were the linear regression and support vector machine.


Subject(s)
Air Pollutants , Air Pollution , Ozone , Ozone/analysis , Air Pollutants/analysis , Peru , Environmental Monitoring/methods , Air Pollution/analysis , Machine Learning
SELECTION OF CITATIONS
SEARCH DETAIL