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Analysis and Predicition of Air Quality And Its Parameters Of Major Metropolitan Cities In India Using ANN

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Varna Vishakar V, Ayush Jain, Gaurav Sharma, Manoj Yadav, Shrey Tiwari, Rajat Sirohi, Mohd Anas
» doi: 10.31838/ecb/2023.12.si6.107


In India's major cities air pollution has grown to be a serious problem for both the environment and human health. In order to estimate the air quality index (AQI) this research article uses artificial neural networks to evaluate the air quality in Delhi, Mumbai, and Chennai three significant metropolises. The AQI is a metric for air quality that shows how dirty the air is in a specific location. In recent years air pollution has grown to be a significant problem in India's main cities. The purpose of this study paper is to evaluate the artificial neural network (ANN)-based air quality index of India's major urban areas. In this study, data on air pollutants (PM10, PM2.5, NO2, SO2, and CO) were gathered from Delhi, Mumbai, and Chennai three of India's largest metropolises. The ANN model was trained and validated using the gathered data. The air quality index of these cities for the year 2021 was subsequently predicted using the ANN model. The study's findings demonstrated that the ANN model is a trustworthy and efficient method for forecasting these cities' air quality indices. The study examines the industrial, vehicular and home air pollution and tracks trends over time using data from a number of sources, including the Central Pollution Control Board, the Indian Meteorological Department, and the National Air Quality Index. The study also examines how affect air quality because were instituted in response to the COVID-19 pandemic.

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