Review on Neural Network Algorithms for Air Pollution Analysis

Neural network is a layer-based optimization technique to solve a real-time problem adjusting the weight values of the neuron based on its activation function. It aids to construct a model to compute optimum results in business analytical process, prediction analysis, financial forecasting, environmental analysis, etc. The environmental analysis are having two approaches namely determine the pollution or identifying the quality using environmental factors such as air, water, and land. The air pollution analysis and predication is to control the pollution. It is a challenging process due to its computational complexity. The environmental research community is working on air pollution factor analysis, pollution index computation, and predication. Present research addresses the findings of various artificial neural network algorithms and presented same. It is recognized that the obtained neural network models are providing sufficient reliable forecast that indicates an effective tool for analyzing and predicting the air pollution. Thus, the study aims to provide various ongoing research results of air pollution analysis and presented the usage of artificial neural network for analysis and prediction of air pollution.