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Application of biomonitoring and support vector machine in water quality assessment

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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.

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Authors and Affiliations

  1. Institute of Information Science and Technology, Ningbo University, Ningbo, 315211, China

    Yue Liao & Jian-yu Xu

  2. Cisco Systems (China) Research and Development Company Limited, Hangzhou, 310012, China

    Zhu-wei Wang

Authors
  1. Yue Liao
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  2. Jian-yu Xu
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  3. Zhu-wei Wang
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Corresponding author

Correspondence to Jian-yu Xu.

Additional information

Project supported by the Natural Science Foundation of Ningbo City (No. 2010A610005) and the Key Science and Technology Program of Zhejiang Province (No. 2011C11049), China

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Liao, Y., Xu, Jy. & Wang, Zw. Application of biomonitoring and support vector machine in water quality assessment. J. Zhejiang Univ. Sci. B 13, 327–334 (2012). https://doi.org/10.1631/jzus.B1100031

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  • DOI: https://doi.org/10.1631/jzus.B1100031

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