Estimation of Air Quality Index of Brajarajnagar and Talcher Industrial Region of Odisha State: A Higher Order Neural Network Approach

Abstract

Economic activities have deteriorated the quality of air, which is a vital natural resource. There has been a lot of research on predicting when terrible air quality will occur, but much of it is limited by a lack of data collected, making it unable to account for periodic and other factors. This article develops and analyses the performances of two higher order neural networks-based forecasts such as pi-sigma neural network (PSNN) and functional link artificial neural network (FLANN) on estimating the air quality index (AQI) of Brarajanagar and Talcher industrial region of Odisha State, India. AQIs at the daily level of two cities are collected from the Kaggle source, preprocessed, and used for modeling and forecasting by the two higher-order neural networks. Simulation outcomes and comparative studies are in favor of PSNN and FLANN-based forecasting