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Title |
Forecasting of Various Air Pollutant Parameters in Bangalore Using Na?ve Bayesian |
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Author |
Shivkumar M, Sudhindra K R, Pranesha T S, Chate D M, Beig G |
| Citation |
Vol. 24 No. 3 pp. 196-200 |
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Abstract |
Weather forecasting is considered to be of utmost important among various important sectors such as flood management and hydro-electricity generation. Although there are various numerical methods for weather forecasting but majority of them are reported to be Mechanistic computationally demanding due to their complexities. Therefore, it is necessary to develop and build models for accurately predicting the weather conditions which are faster as well as efficient in comparison to the prevalent meteorological models. The study has been undertaken to forecast various atmospheric parameters in the city of Bangalore using Na?ve Bayes algorithms. The individual parameters analyzed in the study consisted of wind speed (WS), wind direction (WD), relative humidity (RH), solar radiation (SR), black carbon (BC), radiative forcing (RF), air temperature (AT), bar pressure (BP), PM10 and PM2.5 of the Bangalore city collected from Air Quality Monitoring Station for a period of 5 years from January 2015 to May 2019. The study concluded that Naive Bayes is an easy and efficient classifier that is centered on Bayes theorem, is quite efficient in forecasting the various air pollution parameters of the city of Bangalore. |
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Keywords |
Forecasting, Air pollutant, Na?ve Bayes |
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