Application of biomonitoring and support vector machine in water quality assessment |
| |
Authors: | Yue Liao Jian-yu Xu and Zhu-wei Wang |
| |
Institution: | 1Institute of Information Science and Technology, Ningbo University, Ningbo 315211, China;2Cisco Systems (China) Research and Development Company Limited, Hangzhou 310012, China |
| |
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. |
| |
Keywords: | Water assessment Behavioral feature parameter Support vector machine (SVM) Genetic algorithm (GA) Water quality classification |
本文献已被 SpringerLink 等数据库收录! |
|