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ZJUS-B
Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology)  2012, Vol. 13 Issue (4): 327-334    DOI: 10.1631/jzus.B1100031
New Technique     
Application of biomonitoring and support vector machine in water quality assessment
Yue Liao, Jian-yu Xu, Zhu-wei Wang
Institute of Information Science and Technology, Ningbo University, Ningbo 315211, China; Cisco Systems (China) Research and Development Company Limited, Hangzhou 310012, China
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Abstract  The behavior of schools of zebrafish (Danio rerio) was studied in acute toxicity environments. Behavioral features were extracted and a method for water quality assessment using support vector machine (SVM) was developed. The behavioral parameters of fish were recorded and analyzed during one hour in an environment of a 24-h half-lethal concentration (LC50) of a pollutant. The data were used to develop a method to evaluate water quality, so as to give an early indication of toxicity. Four kinds of metal ions (Cu2+, Hg2+, Cr6+, and Cd2+) were used for toxicity testing. To enhance the efficiency and accuracy of assessment, a method combining SVM and a genetic algorithm (GA) was used. The results showed that the average prediction accuracy of the method was over 80% and the time cost was acceptable. The method gave satisfactory results for a variety of metal pollutants, demonstrating that this is an effective approach to the classification of water quality.

Key words： Water assessment      Behavioral feature parameter      Support vector machine (SVM)      Genetic algorithm (GA)      Water quality classification     
Received: 27 January 2011      Published: 06 April 2012
CLC:  TP183  
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Yue Liao
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Cite this article:

Yue Liao, Jian-yu Xu, Zhu-wei Wang. Application of biomonitoring and support vector machine in water quality assessment. Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology), 2012, 13(4): 327-334.

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http://www.zjujournals.com/xueshu/zjus-b/10.1631/jzus.B1100031     OR     http://www.zjujournals.com/xueshu/zjus-b/Y2012/V13/I4/327

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