Forecasting PM10 in the Bay of Algeciras Based on Regression Models
Research Group PAIDI-TIC-168, Computational Instrumentation and Industrial Electronics (ICEI), Area of Electronics, University of Cádiz, Higher Polytechnic School, Av. Ramón Puyol S/N, E-11202 Algeciras, Spain
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Received: 16 January 2019 / Revised: 1 February 2019 / Accepted: 7 February 2019 / Published: 14 February 2019
Different forecasting methodologies, classified into parametric and nonparametric, were studied in order to predict the average concentration of
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.
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Palomares-Salas, J.C.; González-de-la-Rosa, J.J.; Agüera-Pérez, A.; Sierra-Fernández, J.M.; Florencias-Oliveros, O. Forecasting PM10 in the Bay of Algeciras Based on Regression Models. Sustainability 2019, 11, 968.
Palomares-Salas JC, González-de-la-Rosa JJ, Agüera-Pérez A, Sierra-Fernández JM, Florencias-Oliveros O. Forecasting PM10 in the Bay of Algeciras Based on Regression Models. Sustainability. 2019; 11(4):968.
Palomares-Salas, José C.; González-de-la-Rosa, Juan J.; Agüera-Pérez, Agustín; Sierra-Fernández, José M.; Florencias-Oliveros, Olivia. 2019. "Forecasting PM10 in the Bay of Algeciras Based on Regression Models." Sustainability 11, no. 4: 968.
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