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COVID19: forecasting Air Quality Index and Particulate Matter (PM2.5)

Computers, Materials & Continua 2021年第6期67卷 3363-3380页

作者： R.Mangayarkarasi C.Vanmathi Mohammad Zubair Khan Abdulfattah Noorwali Rachit Jain Priyansh Agarwal School of Information Technology and Engineering Vellore Institute of TechnologyVellore632007India Department of Computer Science College of Computer Science and EngineeringTaibah University41477Saudi Arabia Department of Electrical Engineering Umm Al Qura UniversityMakkah21955Saudi Arabia School of Computer Science and Engineering and Engineering Vellore Institute of TechnologyVellore632007India

Urbanization affects the quality of the air,which has drastically degraded in the past *** quality level is determined by measures of several air pollutant *** create awareness among people,an automation system that forecasts the quality is *** COVID-19 pandemic and the restrictions it has imposed on anthropogenic activities have resulted in a drop in air pollution in various cities in *** overall air quality index(aqi)at any particular time is given as the maximum band for any ***2.5 is a fine particulate matter of a size less than 2.5 micrometers,the inhalation of which causes adverse effects in people suffering from acute respiratory syndrome and other cardiovascular ***2.5 is a crucial factor in deciding the overall *** proposed forecasting model is designed to predict the annual PM2.5 and *** forecasting models are designed using Seasonal Autoregressive Integrated Moving Average and Facebook’s Prophet Library through optimal hyperparameters for better *** aqi category classification model is also presented using classical machine learning *** experimental results confirm the substantial improvement in air quality and greater reduction in PM2.5 due to the lockdown imposed during the COVID-19 crisis.

关键词： aqi PM2.5 COVID19 air quality in India aqi-forecasting

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