Liu Shuming, Che Han, Smith Kate, Chen Chao
School of Environment, Tsinghua University, Beijing, 100084, China,
Environ Monit Assess. 2015 Jan;187(1):4189. doi: 10.1007/s10661-014-4189-4. Epub 2014 Dec 3.
Early warning systems are often used for detecting contamination accidents. Traditional event detection methods suffer from high false negative and false positive errors. This paper proposes a detection method using multiple conventional water quality sensors and introduces a method to determine the values of parameters, which was configured as a multiple optimization problem and solved using a non-dominated sorting genetic algorithm (NSGA-II). The capability of the proposed method to detect contamination events caused by cadmium nitrate is demonstrated in this paper. The performance of the proposed method to detect events caused by different concentrations was also investigated. Results show that, after calibration, the proposed method can detect a contamination event 1 min after addition of cadmium nitrate at the concentration of 0.008 mg/l and has low false negative and positive rates.
早期预警系统常被用于检测污染事故。传统的事件检测方法存在较高的漏报和误报错误。本文提出了一种使用多个传统水质传感器的检测方法，并介绍了一种确定参数值的方法，该方法被配置为一个多目标优化问题，并使用非支配排序遗传算法（NSGA-II）进行求解。本文展示了所提方法检测硝酸镉引起的污染事件的能力。还研究了所提方法检测不同浓度引起的事件的性能。结果表明，经过校准后，所提方法能够在添加浓度为0.008mg/l的硝酸镉后1分钟检测到污染事件，且漏报率和误报率较低。
