Air Quality Prediction Using Machine Learning
DOI:
https://doi.org/10.48001/978-81-966500-7-0-9Keywords:
NSGAII optimized neural network, SOM neural networkair quality predictionAbstract
Evaluating the nature of the air has become essential for inhabitants in numerous modern and metropolitan regions these days. Air quality is significantly impacted by pollution from fuel consumption, transportation, and electricity generation. The build-up of toxic gasses has a negative impact on smart city residents’ quality of life. We require productive air quality observing and forecast models in order to combat the escalating levels of air contamination. These models measure local air contamination and collect data on pollutant concentrations. Particulate matter is made up of tiny solid or liquid particles that can have a serious negative effect on health if inhaled. As a result, assessing and it is turning out to be more significant to anticipate air quality.
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