Ground-level ozone prediction using a neural network model based on meteorological variables and applied to the metropolitan area of Sao Paulo
| Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
|---|---|
| Data(s) |
25/10/2013
25/10/2013
2012
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| Resumo |
A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was developed, based on average values of meteorological variables in the morning (8:00-12:00 hr) and afternoon (13:00-17: 00 hr) periods. Outputs are the maximum and average ozone concentrations in the afternoon (12:00-17:00 hr). The correlation coefficient between computed and measured values was 0.82 and 0.88 for the maximum and average ozone concentration, respectively. The model presented good performance as a prediction tool for the maximum ozone concentration. For prediction periods from 1 to 5 days 0 to 23% failures (95% confidence) were obtained. FAPESP FAPESP CAPES CAPES |
| Identificador |
INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION, GENEVA, v. 49, n. 41306, supl. 1, Part 6, pp. 1-15, AUG, 2012 0957-4352 http://www.producao.usp.br/handle/BDPI/36108 10.1504/IJEP.2012.049730 |
| Idioma(s) |
eng |
| Publicador |
INDERSCIENCE ENTERPRISES LTD GENEVA |
| Relação |
INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION |
| Direitos |
closedAccess Copyright INDERSCIENCE ENTERPRISES LTD |
| Palavras-Chave | #OZONE FORECAST #NEURAL NETWORK #AIR POLLUTION IN MEGACITIES #TROPOSPHERIC OZONE #LARGE URBAN AREAS #BRAZIL #ENVIRONMENTAL SCIENCES |
| Tipo |
article original article publishedVersion |
