Application of biomonitoring and support vector machine in water quality assessment

来源 :Journal of Zhejiang University-Science B(Biomedicine & Biote | 被引量 : 0次 | 上传用户:QQ2009sunboy
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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 de-veloped.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 effec-tive approach to the classification of water quality. The behavior of schools of zebrafish (Danio rerio) was studied in acute toxicity environments. Behavior Features were extracted and a method for water quality assessment using support vector machine (SVM) was de-veloped. 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. Focus 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. method given satisfactory result for a variety of metal pollutants, demonstrating that this is an effec-tive approach to the classification of water quality.
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