Predicting submicron air pollution indicators: A machine learning approach

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Predicting submicron air pollution indicators: A machine learning approach

The regulation of air pollutant levels is rapidly becoming one of the most important tasks for the governments of developing countries, especially China. Submicron particles, such as ultrafine particles (UFP, aerodynamic diameter ≤ 100 nm) and particulate matter ≤ 1.0 micrometers (PM1.0), are an unr...

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Bibliographic Details
Main Authors:	Pandey, G., Zhang, B., Jian, Le
Format:	Journal Article
Published:	Royal Society of Chemistry 2013
Online Access:	http://hdl.handle.net/20.500.11937/5665

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