Air pollution has been a rising concern of the 21st due to its effects to public
health. Air Monitoring Stations are state-of-the-art equipment used to measure
airborne pollutants concentration i.e. carbon monoxide, nitrogen oxide, sulphur
dioxide, particulate matter (PM10) and ozone (O3), as well as the meteorological
parameters (i.e. ambient air temperature, relative humidity, wind speed and
wind direction). Effects of climate change will affect the ambient temperature
and humidity, which may induce a direct effect on air quality. In light of this,
feed forward artificial neural network was employed to simulate the dynamic
variations of PM10 and O3 with relative humidity, temperature, and windspeed
data being the inputs under 12 different training algorithms.

Categories: Kualiti, Partikel Terampai, Udara
Tags: Artikel Jurnal, Data Penerbitan, Sulit