Cedric Lemuel LeeWong Yong JieSenthil Kumar Arumugasamy2024-05-102024-05-102022Lee, C. L., Jie, W. Y., & Arumugasamy, S. K. (2022). Dynamic simulation of airborne pollutant concentrations associated with the effect of climate change in Batu Muda region, Malaysia. Modeling Earth Systems and Environment, 1-16.https://repoemc.ukm.my/handle/123456789/502Air 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.enArtifcial neural networkMultiple input multiple outputClimate changeAir pollutionOzoneParticulate matterJournal