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污染源在线监控数据异常智能检测方法研究
引用本文:江驰,谭斌,黄明祥,谢涛.污染源在线监控数据异常智能检测方法研究[J].环境科学与管理,2016(10):114-117.
作者姓名:江驰  谭斌  黄明祥  谢涛
作者单位:1. 江西省环境信息中心,江西 南昌,330077;2. 环境保护部信息中心,北京,100029;3. 中科宇图科技股份有限公司,北京,100101
摘    要:污染源自动监测数据中存在大量异常数据,严重影响数据整体质量。建立科学可靠的自动监测数据诊断分析处理方法,可有效提升在线监控监管能力水平,为数据的深度应用提供支持。但目前尚缺乏对该方法的深入研究。因此,综述了数据挖掘领域主流异常数据检测方法,并总结了在电力、交通、金融、航天等领域的应用情况,指出存在的不足和发展方向,旨在为智能污染源自动监控数据异常检测提供指导,促进污染源自动监控系统发展。

关 键 词:污染源监控  异常数据  智能检测

Survey Intelligent Anomalies Detecting Methods for Online Monitoring of Pollutant Sources Data
Jiang Chi,Tan Bin,Huang Mingxiang,Xie Tao.Survey Intelligent Anomalies Detecting Methods for Online Monitoring of Pollutant Sources Data[J].Environmental Science and Management,2016(10):114-117.
Authors:Jiang Chi  Tan Bin  Huang Mingxiang  Xie Tao
Abstract:It is common to ind anomalies from automatic monitoring data of pollutant sources, which deteriorates the whole quality of the monitoring data significantly. It can effectively improve the online managing capacity to establish a set o scientific and reliable approaches for detecting, analyzing and handling automatic monitoring data. Furthermore, it can provide support for the further application of automatic monitoring data. But, it still lacks sufficient research on this approach. Therefore, this paper reviews the main anomalies detecting methods in the perspective of data mining and summarizes the important applications of a-nomalies detecting in the fields o power system, transportation, finance, and aerospace. Finally, the shortage and future ersearch direction of anomalies detecting is analyzed. This survey aims to provide a useful guidance for designing intelligent anomalies de-tecting methods of online monitoring data and promote the development of automatic monitoring system of pollutant resources.
Keywords:pollutant resource monitoring  anomaly  intelligent detecting
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