| 引用本文: | 龚瑾玉,颜雪松,胡成玉,龚文引.基于智能优化算法的饮用水污染源定位方法研究综述[J].控制理论与应用,2021,38(9):1313~1323.[点击复制] |
| GONG Jin-yu,YAN Xue-song,HU Cheng-yu,GONG Wen-yin.Survey on methods for drinking water contamination source identification based on intelligent optimization algorithm[J].Control Theory and Technology,2021,38(9):1313~1323.[点击复制] |
|
| 基于智能优化算法的饮用水污染源定位方法研究综述 |
| Survey on methods for drinking water contamination source identification based on intelligent optimization algorithm |
| 摘要点击 3255 全文点击 901 投稿时间：2020-11-20 修订日期：2021-08-21 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 10.7641/CTA.2021.00825 |
| 2021,38(9):1313-1323 |
| 中文关键词 供水管网 水污染 污染源定位 智能计算 多模优化 不确定性 |
| 英文关键词 water supply network water contamination contamination source identification intelligent computing multimodal optimization uncertainty |
| 基金项目 国家自然科学基金项目(U1911205, 62073300, 61673354)资助. |
|
| 中文摘要 |
| 近年来, 突发性饮用水污染事件频繁发生, 严重危害居民生活健康, 通过在饮用水供水管网中布置传感器
对水质进行监测, 能快速识别污染源的位置、质量、发生时间等特征, 有利于有关部门采取措施控制污染扩散, 饮用
水污染源定位研究具有重要的实际意义. 随着智能优化算法在工程问题中的广泛应用, 运用模拟–优化方法求解污
染源定位问题成为当前学者们研究的热门领域. 本文首先给出污染源定位问题的模型和据此抽象出的数学模型, 并
对模拟–优化法求解该问题的一般方法进行了描述. 通过对问题的深入分析, 归纳出污染源定位问题具有多模
性、昂贵性和不确定性, 围绕这3个特性, 重点综述智能优化算法在饮用水污染源定位问题中的代表性研究成果, 最
后指出有待于进一步研究的若干方向和内容. |
| 英文摘要 |
| In recent years, sudden water pollution incidents have occurred frequently, seriously endangering residents’
health. By placing sensors in the water supply networks to monitor the water quality, some characteristics of contamination
source including the location, quality and occurrence time can be quickly identified, which is conducive to the relevant
departments to deal with the diffusion of pollution. Therefore, the research on the contamination source identification has
important practical significance. With the wide application of intelligent optimization algorithms in engineering problems,
using simulation-optimization method to solve contamination source identification problem has become a hot research
field. In this paper, the model of this problem and the abstract mathematical model are given, and then the general method
of solving the problem with simulation-optimization method is described. Through in-depth analysis of this problem, the
paper concludes that it is multimodal, computing expensive and uncertain. Based on these three characteristics, this paper
focuses on the representative research results of intelligent optimization algorithms in contamination source identification
problem, and finally points out some directions and contents to be further studied. |
|
|
|
|
|