摘要
采用非支配排序遗传算法,以水质监测点探测到的不同污染事件的时段区间重叠度最小化和污染事件探测概率最大化为优化目标,结合案例管网计算监测点优化选址方案.算例结果与以污染事件探测及时度最大化和探测概率最大化为目标的优化选址方案相比表明,水质监测点的污染事件探测能力和污染源位置识别能力较高.
Non-dominated 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. This methodology was applied to an example network for optimizing sensor placement in water distribution systems. The solutions obtained were then compared to those optimized by taking into account the probability of detection and time into detection. Results suggest that the proposed method performs better than the benchmark method in detecting a contamination event and identifying its possible source.
出处
《同济大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2013年第5期742-745,共4页
Journal of Tongji University:Natural Science
基金
国家水体污染控制与治理科技重大专项(2012ZX07408002)
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
作者简介
第一作者：刘书明（1976-），男，副研究员，工学博士，主要研究方向为供水管网模型设计与运行最优化。E-mail：shumingliu@tsinghua．edu．cn
