Unsupervised and Supervised Learning based Classification Models for Air Pollution Data

Abstract

As far as, air quality index (AQI) is concerned, the long duration lockdown that was applied in India in year 2020 due to Covid-19 pandemic was very fruitful. The reason being, due to complete ban on the movement of people and automobiles, the air became so pure and clean, and AQI value went much down. The secondary air pollution data of the lockdown duration, for Uttarakhand, is the base of this research work. This work attempts to design unsupervised and supervised classification models to classify the provided data into two classes i.e class 1 (‘clean’) and class 2 (‘hazardous’) using MATLAB. The techniques used are FCM clustering and Probabilistic neural network (PNN). Eventually, a comparative study of the performance of both models is performed.