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  Published Paper Details:

  Paper Title

MACHINE LEARNING APPROACH FOR PREDICTING AND ANALYZING AIR QUALITY

  Authors

  Darshan Gowda T,  G Sudheer Kumar,  Bompally Sriharsh,  Chandan S,  Mrs. Sushmitha S

  Keywords

Keywords- Linear Regression (LR), Random Forest Regression (RF), Back Propagation Neural Network (BPN), Decision Tree Regression (DTR), Root Mean Square Error (RMSE), Support Vector Machine (SVM), Mean Absolute Error (MAE)

  Abstract


India has gained international attention as a result of its air pollution. The nation's rising air pollution has been one of the key concerns for both the government and the populace. We provide a comprehensive and useful approach for resolving the Air Quality Analysis in this study using machine learning techniques. This article uses information from numerous meteorological stations to calculate the Air Quality Index (AQI) for India. On the gathered data, we are applying machine learning methods including support vector machines, back propagation neural networks, decision trees, and linear regression (SVM). To assess accuracy of many models, we used the root mean square (RMS) approach.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2212592

  Paper ID - 229463

  Page Number(s) - f207-f211

  Pubished in - Volume 10 | Issue 12 | December 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Darshan Gowda T,  G Sudheer Kumar,  Bompally Sriharsh,  Chandan S,  Mrs. Sushmitha S,   "MACHINE LEARNING APPROACH FOR PREDICTING AND ANALYZING AIR QUALITY", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 12, pp.f207-f211, December 2022, Available at :http://www.ijcrt.org/papers/IJCRT2212592.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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