Applying Artificial Neural Networks to Short-Term PM2.5 Forecasting Modeling-Reference-Cited by-同舟云学术

Applying Artificial Neural Networks to Short-Term PM2.5 Forecasting Modeling

Published:2016 Issue: Volume: Page:204-211
ISSN:1868-4238
Container-title:IFIP Advances in Information and Communication Technology
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Author:

Oprea Mihaela,Mihalache Sanda Florentina,Popescu Marian

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-44944-9_18

Reference18 articles.

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3. Baker, K.R., Foley, K.M.: A nonlinear regression model estimating single source concentrations of primary and secondarily formed PM2.5. Atmos. Environ. 45, 3758–3767 (2011)

4. Advances in Intelligent Systems and Computing;A Nebot,2014

5. Oprea, M., Dragomir, E.G., Mihalache, S.F., Popescu, M.: Prediction methods and techniques for PM2.5 concentration in urban environment (in Romanian). In: Iordache, S., Dunea, D. (eds.) Methods to Assess the Effects of Air Pollution with Particulate Matter on Children’s Health (in Romanian), pp. 387–428. MatrixRom, Bucharest (2014)

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