ISSN 2394-5125
 

Research Article 


AN EMPIRICAL STUDY OF MACHINE LEARNING TECHNIQUES FOR AIR QUALITY PREDICTION

Anushka Chadha, Dr. Sumita Gupta.

Abstract
Air pollution is posing serious health threats and environmental hazards in today’s world. It does not only degrade the quality of life but also affects the economy by decreasing the productivity rate. Forecasting the quality of air beforehand will enable the governing authorities to make necessary decisions in case the air quality starts tending towards the serious category. This knowledge will help to achieve and maintain cleaner air in metropolitan cities. In this paper, air quality index of Indian cities has been forecasted. The time series model is employed to predict individual concentration of each major pollutant causing air pollution. Based on this data, two regression techniques have been used to predict the air quality index. Furthermore, a comparative analysis of these techniques has been done to determine better model for predicting the quality of air. The comparisons were made based on error rate that has been calculated using the accuracy metrics which includes Mean Absolute Error (MAE) and Root Mean Square Error (RMSE).

Key words: Air quality index (AQI), Random forest, Decision tree, Time series, Machine learning


 
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Pubmed Style

Anushka Chadha, Dr. Sumita Gupta. AN EMPIRICAL STUDY OF MACHINE LEARNING TECHNIQUES FOR AIR QUALITY PREDICTION. JCR. 2020; 7(18): 1468-1475. doi:10.31838/jcr.07.18.189


Web Style

Anushka Chadha, Dr. Sumita Gupta. AN EMPIRICAL STUDY OF MACHINE LEARNING TECHNIQUES FOR AIR QUALITY PREDICTION. http://www.jcreview.com/?mno=95838 [Access: July 09, 2020]. doi:10.31838/jcr.07.18.189


AMA (American Medical Association) Style

Anushka Chadha, Dr. Sumita Gupta. AN EMPIRICAL STUDY OF MACHINE LEARNING TECHNIQUES FOR AIR QUALITY PREDICTION. JCR. 2020; 7(18): 1468-1475. doi:10.31838/jcr.07.18.189



Vancouver/ICMJE Style

Anushka Chadha, Dr. Sumita Gupta. AN EMPIRICAL STUDY OF MACHINE LEARNING TECHNIQUES FOR AIR QUALITY PREDICTION. JCR. (2020), [cited July 09, 2020]; 7(18): 1468-1475. doi:10.31838/jcr.07.18.189



Harvard Style

Anushka Chadha, Dr. Sumita Gupta (2020) AN EMPIRICAL STUDY OF MACHINE LEARNING TECHNIQUES FOR AIR QUALITY PREDICTION. JCR, 7 (18), 1468-1475. doi:10.31838/jcr.07.18.189



Turabian Style

Anushka Chadha, Dr. Sumita Gupta. 2020. AN EMPIRICAL STUDY OF MACHINE LEARNING TECHNIQUES FOR AIR QUALITY PREDICTION. Journal of Critical Reviews, 7 (18), 1468-1475. doi:10.31838/jcr.07.18.189



Chicago Style

Anushka Chadha, Dr. Sumita Gupta. "AN EMPIRICAL STUDY OF MACHINE LEARNING TECHNIQUES FOR AIR QUALITY PREDICTION." Journal of Critical Reviews 7 (2020), 1468-1475. doi:10.31838/jcr.07.18.189



MLA (The Modern Language Association) Style

Anushka Chadha, Dr. Sumita Gupta. "AN EMPIRICAL STUDY OF MACHINE LEARNING TECHNIQUES FOR AIR QUALITY PREDICTION." Journal of Critical Reviews 7.18 (2020), 1468-1475. Print. doi:10.31838/jcr.07.18.189



APA (American Psychological Association) Style

Anushka Chadha, Dr. Sumita Gupta (2020) AN EMPIRICAL STUDY OF MACHINE LEARNING TECHNIQUES FOR AIR QUALITY PREDICTION. Journal of Critical Reviews, 7 (18), 1468-1475. doi:10.31838/jcr.07.18.189





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