A Neural Network Forecasting System For Daily
Air Quality Index In Macau
Author(s)
K.M. Mok, S.C. Tarn, P. Van & L.H. Lam
Abstract
Using the data recorded at the Northern Zone monitoring air-quality monitoring
station at Macau during April to June of 1999 as the training and testing data set,
a three-layered feed-forward neural network is developed to predict the one-day
ahead daily air quality index (AQI) at that area. Various input selection ranging
from using the past three day measurements to the past twelve day
measurements are tested against different number of hidden layer neurons. It is
found experimentally that using only the past three days values as input with 8
neurons in the hidden layer give the best testing results. This setting is adopted
as the basic setting of the developed model. It is then applied to forecast the sub-
index of each measured pollutant and the predicted AQI is set as the maximum
o
Keywords
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