An Artificial Neural Network Forecast of SO2 Air Contamination: A Case Study of Ghaziabad City

One of the pollutants in the air that contributes most to air pollution is SO2. Artificial neural networks, a popular learning technique currently in use, were used in this study to assess the effects of this toxin on the environment and human health using data from 2019 to 2023. The Air Observation Centre of Uttar Pradesh Pollution Control Board (UPPCB) obtained information related to the Ghaziabad region, which is home to the industrial hub. SPSS programming was then used to complete the modelling and optimization processes. Before the generated SO2 estimation results were compared with the real data, they underwent a multilayer perceptron analysis. Moreover, the province of Ghaziabad's SO2 value has occasionally been reported to be higher than allowed, especially during times of high production.