Research Journal of Chemistry

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A neural network approach to forecast particulate matter concentration in Manali area of Chennai City

Nadeem Imran and Sheik Uduman P.S.

Res. J. Chem. Environ; Vol. 27(8); 35-42; doi:; (2023)

Air pollution is one of the threatening menaces confronting all over the globe in recent decades. Among the air pollutants, PM2.5 is one of the major alarming components rising at a rapid pace in the metropolitan city of Chennai due to the fast expansion of industrialization and urbanization. An early observation for tackling the rise in particulate matter concentration (PM2.5) levels requires precise prediction.

In this regard, the present study employs a Multilayer Perception Neural Network (MLPNN) technique using the Levenberg-Marquardt optimisation training algorithm for forecasting the one-day concentration PM2.5. The model evaluation statistics R2 and index of the agreement have been utilized for assessing the forecasting accuracy. The results confirm that the ANN6 model is the most suitable for acquiring the almost error-free model to achieve real-time forecasting of PM2.5 concentration.