LVQ Based Classification of Air Quality Using Data for Lockdown Period of COVID-19

摘要

The lockdown duration of COVID-19 gave rise to a significant betterment in AQI (Air Quality Index) worldwide. In the present research paper, binary classification problem of the air pollutants data of Uttarakhand, India, for year 2019 and 2020 (lockdown period), has been addressed. This problem is challenging to solve as it is non-linearly separable. Using this data, a neural network has been trained, to perform classification, using competitive learning technique (unsupervised learning). Then, for achieving better classification results, a supervised learning technique, learning vector quantization algorithm (LVQ), is used. Finally, the performance of both the networks is compared. All results are obtained in MATLAB.