Predicting Air Pollutant using Data Mining and Machine Learning Algorithms

Authors

  • Isha Jagtap
  • Prof. Nandini Babbar

DOI:

https://doi.org/10.46243/jst.2021.v6.i04.pp25-30

Keywords:

Decision Tree, Support Vector Machine, Artificial neural network, Data Mining

Abstract

Air pollution can be defined presence of harmful or hazardous substances in the air which deteriorate the quality of air. As we are moving ahead in future the environment is getting polluted day by day due to these biological molecules and harmful gases. These pollutant causes diseases, allergy, etc and death as well. The main aim of this article is to study data mining and machine learning algorithms for predicting air pollutants, especially PM2.5 .So as to control the emission of these harmful substances This is a scientific approach for predicting PM2.5 level in the air using a data set containing different attributes.

 

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Published

2021-08-16

How to Cite

Isha Jagtap, & Prof. Nandini Babbar. (2021). Predicting Air Pollutant using Data Mining and Machine Learning Algorithms. Journal of Science & Technology (JST), 6(Special Issue 1), 25–30. https://doi.org/10.46243/jst.2021.v6.i04.pp25-30

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