Forecasting air quality index based on Mamdani fuzzy inference system

This paper aims to establish a non-linear regression model based on Mamdani fuzzy inference system and examine the performance of the model based on various metrics such as correlation, index of agreement, mean absolute percentage error, mean absolute error and root mean square error. The data used in this operation is collected from Delhi Punjabibagh with pollutants spanning from Nitrogen dioxide to particulate matter 10μm with ozone and carbon monoxide considered to comprehensively cover the base of inputs. The resultant air quality index is then measured with the calculated ones based on the metrics discussed above.