title: Application of biomonitoring and support vector machine in water quality assessment.
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 (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.
authors.affiliation: Institute of Information Science and Technology, Ningbo University, Ningbo 315211, China.
authors.forename: Yue
authors.initials: Y
authors.lastname: Liao
authors.forename: Jian-yu
authors.initials: JY
authors.lastname: Xu
authors.forename: Zhu-wei
authors.initials: ZW
authors.lastname: Wang
mesh_terms: D000818:Animals; D001522:Behavior, Animal / Q000187:drug effects* / Q000502:physiology; D001681:Biological Assay / Q000379:methods*; D004784:Environmental Monitoring / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods; D060388:Support Vector Machine; D014867:Water / Q000032:analysis* / Q000737:chemistry / Q000494:pharmacology*; D015027:Zebrafish / Q000502:physiology*
chemical_list: D014867:Water