Author(s): P. Perez
According to the value of the 24-hour average of PM10 concentration calculated
every hour, three levels of increasing potential harm for the population of
Santiago, Chile are defined: alert between 195 and 239, pre-emergency between
240 and 329 and emergency above 330 ^g/nf.
We have developed a neural
network based model that uses past values of PM10 concentrations plus
forecasted values of meteorological variables as input in order to predict the level
reached by the maximum of the 24-hour average of PM10 concentration on the
We have adjusted the parameters of the model using 1994 data and
tested it with 1995 data.
By comparing the results of the model with actual data
we obtain an overall efficiency of 85%.
Correct predictions of high level cases
may be increased by giving more weight to the sample cases, g...
Size: 689 kb
Paper DOI: 10.2495/AIR010161
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