| Application of biomonitoring and support vector machine in water quality assessment. | |
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MedLine Citation:
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PMID: 22467374 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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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 (LC(50)) 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 (Cu(2+), Hg(2+), Cr(6+), and Cd(2+)) 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:
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Yue Liao; Jian-Yu Xu; Zhu-Wei Wang |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Journal of Zhejiang University. Science. B Volume: 13 ISSN: 1862-1783 ISO Abbreviation: J Zhejiang Univ Sci B Publication Date: 2012 Apr |
Date Detail:
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Created Date: 2012-04-02 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101236535 Medline TA: J Zhejiang Univ Sci B Country: China |
Other Details:
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Languages: eng Pagination: 327-34 Citation Subset: IM |
Affiliation:
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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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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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