Study Of Machine Learning Models For Air Quality Index Prediction

  • Shanthi S, Nirmaladevi K , Pyingkodi M , Deepika K, Gobinath R

Abstract

Air pollutant has becoming an significant environment threat in recent days. Forecasting of Air Quality Index (AQI) and concentration of air pollutant plays a vital role in warning people about to control the air pollutant. Machine learning regression models namelyMultiple Linear Regression, Decision Tree Regression, Random Forest Regression and Support Vector Machine Regression are used to forecast the AQI. The performance of these models is evaluated using the different statistical measures namely Coefficient of Mean Square, Root Mean Squared Error, Mean Absolute Error and Root Mean Squared Log Error. This study is evaluated with the publically available dataset and obtains the significant results.

Published
2020-05-01
How to Cite
Shanthi S, Nirmaladevi K , Pyingkodi M , Deepika K, Gobinath R. (2020). Study Of Machine Learning Models For Air Quality Index Prediction . International Journal of Control and Automation, 13(03), 203-208. Retrieved from https://sersc.org/journals/index.php/IJCA/article/view/24987