Abstract
Many countries are suffering from air pollution due to imbalanced urbanization, unregulated increase in transportation, and inorganic industrialization. Air pollution directly affects the ecosystem and climate thereby compromising the well-being of the citizens and cities. For this reason, predicting air pollution in advance has a great importance in supporting proactive plans and environmental management actions for decision makers. In the literature, many research efforts are focusing on predicting air pollutant concentrations. In this chapter, we present recent artificial intelligence-based air pollution prediction approaches. In this context, we comprehensively reviewed the literature and categorized the proposed prediction methods based on feature selection methods, air pollutant types, and learning models.
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