Algorithms for pollutants forecasting

Abstract

The impact of pollution on human health is very well known and affects more and more economic and social activities. Since the authorities do not always have the necessary equipment and trained personnel for pollution monitoring, we observed the need to develop algorithms for approximating different polluting values. This paper is a review of the main algorithmic approaches to estimate pollutant values. Most of the proposed approaches are based on machine learning, neural networks and decision trees.