FORECASTING OF DAILY PM10 USING LONG SHORT TERM MEMORY NEURAL NETWORK IN GANGA NAGAR, MEERUT INDIA FOR HEALTH AND AGRICULTURE APPLICATIONS

Abstract

Air quality is known to significantly affect health, forecasting it is a very important task. A highly industrialized region in India, Meerut has one of the most extensive agricultural applications. Delhi, India’s central pollution control board keeps time series data. In order to predict PM 2.5 one day in advance, a Long Short Term Memory Network is used. The findings demonstrate that PM 2.5 is predicted more accurately. This study is interesting because it can be used by government agencies, businesses, and citizens alike to make informed decisions.