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Prediction and Analysis of Air Pollution Using Machine Learning


Air pollution is one of the most dangerous forms of pollution. We aim to find the pollution prediction and the air quality in Kerala, India. Through this paper, machine learning algorithms such as ridge regression, linear regression, random forest regression, LASSO regression, and elastic net regression are opted for analyzing and predicting air quality. This analysis helps to dissect how it will be beneficial to industrial sectors in the conversion of pollutants into a useful by-product.

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We, Megha Satish and Manju Murali, are grateful to the Kerala State Pollution Control Board Ernakulam for providing the data.


The authors declared that no funding was received for this research.

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Correspondence to Manju Murali.

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This article is part of the topical collection “Intelligent Systems guest edited by Geetha Ganesan, Lalit Garg, Renu Dhir, Vijay Kumar and Manik Sharma”.

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Murali, M., Satish, M. & Rajalakshmi, V.R. Prediction and Analysis of Air Pollution Using Machine Learning. SN COMPUT. SCI. 3, 483 (2022).

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  • Ridge regression
  • Linear regression
  • Random forest regression
  • LASSO regression
  • Elastic net regression