摘要
针对供水管网水质监测点的优化选址问题,提出污染源位置识别准确度的概念,以水质监测点探测到的不同污染事件的时段区间冗余度最小化,和污染事件探测概率最大化为优化目标,结合一个案例管网,采用非支配排序遗传算法计算节点用水量变化条件下的监测点优化选址方案,算例结果显示节点用水量的不确定性不显著影响监测点的污染事件探测能力和可能性节点识别能力,但使监测点的污染源位置识别准确度降低.
The notion of identification fitness was proposed for optimizing sensor placement in water distribution systems.Nondominated Sorting Genetic Algorithm Ⅱ was used to find the Pareto front between minimum overlap of possible detection times of two events and the best probability of detection,taking nodal demand uncertainties into account.This methodology was applied to an example network.The solutions show that the probability of detection and the number of possible locations are not remarkably affected by nodal demand uncertainties,but the sources identification accuracy declines with nodal demand uncertainties.
出处
《环境科学》
EI
CAS
CSCD
北大核心
2013年第8期3108-3112,共5页
Environmental Science
基金
国家水体污染控制与治理科技重大专项(2012ZX07408-002)
清华大学自主科研项目
关键词
供水管网系统
水质
监测点
多目标优化
污染源位置识别
water distribution systems water quality monitors multi-objective optimization source identification
