Air Quality Index Prediction using Linear Regression and ANFIS

This research is addressing a very critical parameter Air Quality Index (AQI) having a severe impact on human health. The management of AQI is of utmost importance in existing environmental discourse, demanding reliable and accurate prediction models for AQI. This research is contributing considerably in this area by exploring two different approaches of AQI prediction modeling. One is the classical approach which is known for its simplicity that is Linear Regression model. Another one is a more advanced technique, integrating fuzzy logic & neural networks, named Adaptive Neuro-Fuzzy Inference System (ANFIS) model. MATLAB has been used as a primary tool for developing and analyzing the models.