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Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 397473, 12 pages
http://dx.doi.org/10.1155/2012/397473
Research Article

Freshwater Algal Bloom Prediction by Support Vector Machine in Macau Storage Reservoirs

1Faculty of Science and Technology, University of Macau, Taipa, Macau
2Laboratory & Research Center, Macao Water Supply Co. Ltd., Conselheiro Borja, Macau

Received 26 August 2012; Accepted 11 November 2012

Academic Editor: Sheng-yong Chen

Copyright © 2012 Zhengchao Xie et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Understanding and predicting dynamic change of algae population in freshwater reservoirs is particularly important, as algae-releasing cyanotoxins are carcinogens that would affect the health of public. However, the high complex nonlinearity of water variables and their interactions makes it difficult to model the growth of algae species. Recently, support vector machine (SVM) was reported to have advantages of only requiring a small amount of samples, high degree of prediction accuracy, and long prediction period to solve the nonlinear problems. In this study, the SVM-based prediction and forecast models for phytoplankton abundance in Macau Storage Reservoir (MSR) are proposed, in which the water parameters of pH, SiO2, alkalinity, bicarbonate , dissolved oxygen (DO), total nitrogen (TN), UV254, turbidity, conductivity, nitrate, total nitrogen (TN), orthophosphate , total phosphorus (TP), suspended solid (SS) and total organic carbon (TOC) selected from the correlation analysis of the 23 monthly water variables were included, with 8-year (2001–2008) data for training and the most recent 3 years (2009–2011) for testing. The modeling results showed that the prediction and forecast powers were estimated as approximately 0.76 and 0.86, respectively, showing that the SVM is an effective new way that can be used for monitoring algal bloom in drinking water storage reservoir.