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Published in:

Volume 7 Issue 3
March-2020
eISSN: 2349-5162

Unique Identifier

JETIR2003302

Page Number

6-8

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Title

Air Pollution Prediction Using ML

ISSN

2349-5162

Cite This Article

"Air Pollution Prediction Using ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 3, page no.6-8, March-2020, Available :http://www.jetir.org/papers/JETIR2003302.pdf

Abstract

Due to large scale industrialization and advances in technology there has been increased pressure on mother nature. This includes air pollution that is somewhat like a bad omen for humanity. There have been a lot of steps taken to reduce pollution but it has been of no avail. To provide a solution to this ongoing crisis, there needs to be some kind of air pollution level prediction technique that can be utilized. To get a successful prediction Machine Learning is the best option. The prediction through Machine Learning is one of the most accurate and the cost effective technique, but eventually this technique needs high end algorithms and technique to estimate the same. So this review paper basically concentrates on understanding of the all the novel methods existed in the prediction of air pollution and try to find the gaps in them to provide a better solution in the research domain.

Key Words

Air pollution, Machine Learning, Pollution Prediction.

Cite This Article

"Air Pollution Prediction Using ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 3, page no. pp6-8, March-2020, Available at : http://www.jetir.org/papers/JETIR2003302.pdf

Publication Details

Published Paper ID: JETIR2003302
Registration ID: 230185
Published In: Volume 7 | Issue 3 | Year March-2020
DOI (Digital Object Identifier):
Page No: 6-8
ISSN Number: 2349-5162

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Cite This Article

"Air Pollution Prediction Using ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 3, page no. pp6-8, March-2020, Available at : http://www.jetir.org/papers/JETIR2003302.pdf




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