Please use this identifier to cite or link to this item:
|Title:||ANN application for prediction of atmospheric nitrogen deposition to aquatic ecosystems|
|Authors:||Palani, S. |
|Source:||Palani, S., Tkalich, P., Balasubramanian, R., Palanichamy, J. (2011-06). ANN application for prediction of atmospheric nitrogen deposition to aquatic ecosystems. Marine Pollution Bulletin 62 (6) : 1198-1206. ScholarBank@NUS Repository. https://doi.org/10.1016/j.marpolbul.2011.03.033|
|Abstract:||The occurrences of increased atmospheric nitrogen deposition (ADN) in Southeast Asia during smoke haze episodes have undesired consequences on receiving aquatic ecosystems. A successful prediction of episodic ADN will allow a quantitative understanding of its possible impacts. In this study, an artificial neural network (ANN) model is used to estimate atmospheric deposition of total nitrogen (TN) and organic nitrogen (ON) concentrations to coastal aquatic ecosystems. The selected model input variables were nitrogen species from atmospheric deposition, Total Suspended Particulates, Pollutant Standards Index and meteorological parameters. ANN models predictions were also compared with multiple linear regression model having the same inputs and output. ANN model performance was found relatively more accurate in its predictions and adequate even for high-concentration events with acceptable minimum error. The developed ANN model can be used as a forecasting tool to complement the current TN and ON analysis within the atmospheric deposition-monitoring program in the region. © 2011 Elsevier Ltd.|
|Source Title:||Marine Pollution Bulletin|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 5, 2017
WEB OF SCIENCETM
checked on Nov 16, 2017
checked on Dec 10, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.