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- Title
Forecasting PM10 in the Bay of Algeciras Based on Regression Models.
- Authors
Palomares-Salas, José Carlos; González-de-la-Rosa, Juan José; Agüera-Pérez, Agustín; Sierra-Fernández, José María; Florencias-Oliveros, Olivia
- Abstract
Different forecasting methodologies, classified into parametric and nonparametric, were studied in order to predict the average concentration of P M 10 over the course of 24 h. The comparison of the forecasting models was based on four quality indexes (Pearson's correlation coefficient, the index of agreement, the mean absolute error, and the root mean squared error). The proposed experimental procedure was put into practice in three urban centers belonging to the Bay of Algeciras (Andalusia, Spain). The prediction results obtained with the proposed models exceed those obtained with the reference models through the introduction of low-quality measurements as exogenous information. This proves that it is possible to improve performance by using additional information from the existing nonlinear relationships between the concentration of the pollutants and the meteorological variables.
- Subjects
PARTICULATE matter; AIR pollutants; REGRESSION analysis
- Publication
Sustainability (2071-1050), 2019, Vol 11, Issue 4, p968
- ISSN
2071-1050
- Publication type
Article
- DOI
10.3390/su11040968