Predicting Particulate Matter (PM2.5) Concentrations in the Air of Shahr-e Ray City, Iran, by Using an Artificial Neural Network.

Autor:	Asadollahfardi, Gholamreza1, Madinejad, Mahdi1, Aria, Shiva Homayoun1, Motamadi, Vahid1
Předmět:	*Air pollution forecasting *Particulate matter *Air pollution *Health *Air quality management Artificial neural networks
Zdroj:	Environmental Quality Management. Summer2016, Vol. 25 Issue 4, p71-83. 13p. 2 Charts, 6 Graphs.
Abstrakt:	Particulate matter (PM), along with other air pollutants, pose serious hazards to human health. The Artificial Neural Network (ANN) is a branch of artificial intelligence that has an ability to make accurate predictions. In this article, the authors describe such methods and how historical data on air quality, moisture, wind velocity, and temperature in Shahr‐e Ray City, located at the southern tip of Tehran, was used to train an ANN to provide accurate predictions of PM concentrations. The availability of such predictions can offer significant assistance to those who are working to reduce air pollution. [ABSTRACT FROM AUTHOR]
Databáze:	GreenFILE
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