The Hybrid Method to Predict Biochemical Oxygen Demand of Haihe River in China

Xuan Zhang; Hong Lei Jiang; Yao Zong Zhang

doi:10.4028/www.scientific.net/AMR.610-613.1066

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Synthesis of Two Different Sizes of CdTe Quantum Dots for Detection of Copper(II) in Seawater
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 610-613The Hybrid Method to Predict Biochemical Oxygen...

The Hybrid Method to Predict Biochemical Oxygen Demand of Haihe River in China

Abstract:

In order to predict the biochemical oxygen demand (BOD) concentration of Haihe River, a more accurate hybrid model, based on combined principal component regression (PCR) and artificial neural networks (ANN), was constructed. Data on nine water variables from 2007 to 2008 were used to develop models. The hybrid method achieved more accurate prediction compared with PCR and ANN. The R² values were 0.762, 0.815 and 0.927 for PCR, ANN and the hybrid method, respectively. In a case application, the predictions of the hybrid method were found to been consistent with the observed values from January to June in 2009, while the predictions of PCR and ANN did not fit well for sample site 4 and 5.

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Periodical:

Advanced Materials Research (Volumes 610-613)

Pages:

1066-1069

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.610-613.1066

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Online since:

December 2012

Authors:

Xuan Zhang, Hong Lei Jiang, Yao Zong Zhang

Keywords:

Artificial Neural Network (ANN), Biochemical Oxygen Demand, Hybrid Method, Principal Component Regression

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