Title :
Forecasting tropospheric ozone concentrations with adaptive neural networks
Author :
Taormina, R. ; Mesin, L. ; Orione, F. ; Pasero, E.
Author_Institution :
Dept. of Civil & Struct. Eng., Hong Kong Polytech. Univ., Hong Kong, China
fDate :
July 31 2011-Aug. 5 2011
Abstract :
The issue of air quality is now a major concern for many citizens worldwide. Local air quality forecasting can be made on the basis of meteorological variables and air pollutants concentration time series. We propose an adaptive filter technique based on an artificial neural network (ANN) to make 24-hours maximal daily ozone-concentrations forecasts.
Keywords :
air pollution; environmental science computing; neural nets; adaptive filter technique; adaptive neural networks; air pollutants concentration time series; air quality forecasting; artificial neural network; meteorological variable; ozone-concentration forecast; tropospheric ozone concentration forecasting; Air pollution; Artificial neural networks; Atmospheric modeling; Data models; Neurons; Time series analysis; Training;
Conference_Titel :
Neural Networks (IJCNN), The 2011 International Joint Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-9635-8
DOI :
10.1109/IJCNN.2011.6033450
