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计算机系统应用英文版:2020,29(7):139-144
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基于改进AFSA算法的河流突发水污染溯源
(1.中国科学院大学, 北京 100049;2.中国科学院 沈阳计算技术研究所, 沈阳 110168;3.辽宁省生态环境监测中心, 沈阳 110161;4.阜新市生态环境保护服务中心, 阜新 123000)
Traceability Method of Sudden River Water Pollution Based on Improved AFSA Algorithm
(1.University of Chinese Academy of Sciences, Beijing 100049, China;2.Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China;3.Liaoning Ecological Environment Monitoring Center, Shenyang 110161, China;4.Fuxin Ecological Environmental Protection Service Center, Fuxin 123000, China)
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Received:December 21, 2019    Revised:January 29, 2020
中文摘要: 污染源的排放时间、排放位置以及排放总量的确定是河流突发性水污染溯源问题的关键.如何快速准确的确定重金属污染源的三个因素, 然后通过GIS得到污染源企业的排查清单是本文的研究重点.本文通过对河流的水文水质的研究, 依据重金属污染物的特性, 确定了一维河流重金属污染物的时空变化的动态解析解.同时构造了污染物时空溯源模型以及污染物排放总量模型, 并利用改进的AFSA算法实现了模型的求解.研究结果表明, 该算法使得模型能够更加快速准确地得到三个参数的结果, 然后将该结果通过本文的方法并且借助GIS技术更快更准确的为相关工作人员提供污染源企业概率排查清单.本文提出的方法和模型对于水污染处理以及保护水环境具有一定的指导意义.
中文关键词: 突发性水污染  重金属  AFSA算法  溯源  GIS
Abstract:The key to solve the problem of tracing the source of sudden water pollution in rivers is to determine its discharge time, location, and total amount. This study proposes two models which can quickly and accurately determine these three factors of heavy metal pollution sources and obtain the list of pollution sources through GIS. This study determines the dynamic analytical solution for the spatiotemporal changes of heavy metal pollutants in one-dimensional rivers, through the study of the hydrological and water quality of rivers and the characteristics of heavy metal pollutants. At the same time, a spatial-temporal traceability model of pollutants and a total pollutant discharge model are constructed, and this models are solved using the improved AFSA algorithm. The research results show that the algorithm enables the model to obtain the results of the three parameters more quickly and accurately, and then passes the results through the proposed method and uses GIS technology to provide the relevant staff with a probabilistic checklist of pollution source enterprises more quickly and accurately. The methods and models proposed in this study have certain guiding significance for water pollution treatment and protection of the water environment.
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基金项目:国家科技重大专项(2018ZX07601001)
引用文本:
李欣欣,王宁,姜秋俚,刘枢,魏建勋,张楠.基于改进AFSA算法的河流突发水污染溯源.计算机系统应用,2020,29(7):139-144
LI Xin-Xin,WANG Ning,JIANG Qiu-Li,LIU Shu,WEI Jan-Xun,ZHANG Nan.Traceability Method of Sudden River Water Pollution Based on Improved AFSA Algorithm.COMPUTER SYSTEMS APPLICATIONS,2020,29(7):139-144