Aircraft pollutant emissions are an
important part of sources of pollution that directly or indirectly affect human
health and ecosystems. This research suggests an Artificial Neural Network
model to determine the healthy risk level around Soekarno Hatta International
Airport-Cengkareng
Indonesia. This ANN modeling is a flexible method, which enables to recognize
highly complex non-linear correlations. The network was trained with real
measurement data and updated with new measurements, enhancing its quality and
making it the ideal method for this research. Measurements of aircraft
pollutant emissions are carried out with the aim to be used as input data and
to validate the developed model. The obtained results concerned the improved
ANN architecture model based on pollutant emissions as input variables. ANN
model processes variables—hidden layers—and gives an
output variable corresponding to a healthy risk level. This model is
characterized by
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