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Vol. 172, Issue 6, June 2014, pp. 290-294

 

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An Artificial Neural Network Based Short-term Dynamic Prediction of Algae Bloom
 

Yao Junyang, * Shi Yan, Wang Xiaoyi, Xu Jiping

Beijing Technology & Business University, College of Computer and Information Engineering, Beijing, 100048, China
Tel.: 13691215263

* E-mail: shiyanspring@126.com

 

Received: 11 April 2014 /Accepted: 30 May 2014 /Published: 30 June 2014

Digital Sensors and Sensor Sysstems

 

Abstract: This paper proposes a method of short-term prediction of algae bloom based on artificial neural network. Firstly, principal component analysis is applied to water environmental factors in algae bloom raceway ponds to get main factors that influence the formation of algae blooms. Then, a model of short-term dynamic prediction based on neural network is built with the current chlorophyll_a values as input and the chlorophyll_a values in the next moment as output to realize short-term dynamic prediction of algae bloom. Simulation results show that the model can realize short-term prediction of algae bloom effectively.

 

Keywords: Algae bloom prediction, Principal component analysis (PCA), Radial basis function neural (RBF) network.

 

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