Blue Eyes Intelligence Engineering & Sciences Publication(BEIESP)
T. R. Saravanan
V. Pavithra
G.Saranya
2020-04-30
<p>Generally, air pollution refer to the release of various pollutants into the air which are threatening the human health and planet as well. The air pollution is the major dangerous vicious to the humanity ever faced. It causes major damage to animals, plants etc., if this keeps on continuing, the human being will face serious situations in the upcoming years. The major pollutants are from the transport and industries. So, to prevent this problem major sectors have to predict the air quality from transport and industries .In existing project there are many disadvantages. The project is about estimating the PM2.5 concentration by designing a photograph based method. But photographic method is not alone sufficient to calculate PM2.5 because it contains only one of the concentration of pollutants and it calculates only PM2.5 so there are some missing out of the major pollutants and the information needed for controlling the pollution .So thereby we proposed the machine learning techniques by user interface of GUI application. In this multiple dataset can be combined from the different source to form a generalized dataset and various machine learning algorithms are used to get the results with maximum accuracy. From comparing various machine learning algorithms we can obtain the best accuracy result. Our evaluation gives the comprehensive manual to sensitivity evaluation of model parameters with regard to overall performance in prediction of air high quality pollutants through accuracy calculation. Additionally to discuss and compare the performance of machine learning algorithms from the dataset with evaluation of GUI based user interface air quality prediction by attributes.</p>
https://doi.org/10.35940/ijeat.D6782.049420
oai:zenodo.org:5554333
eng
Zenodo
issn:2249-8958
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
International Journal of Engineering and Advanced Technology (IJEAT), 9(4), 516-521, (2020-04-30)
pollutants dataset, GUI results, machine learning, supervised algorithm.
Air Quality Prediction by Classification of Supervised Machine Learning
info:eu-repo/semantics/article