计算机应用研究2016，Vol.33Issue(8)：2353-2357,5.DOI:10.3969/j.issn.1001-3695.2016.08.026
基于模糊聚类的 CO2数据流时空异常模式的研究
Fuzzy cluster based approach for spatial-temporal anomaly detection over CO2 data streams
摘要
Abstract
In view of the traditional anomaly detection algorithms could not identify CCS abnormal monitoring data types,so in order to identify the CO2 data streams anomalies caused by leakage,this paper proposed a fuzzy clustering based approach for spatial-temporal anomaly detection over CO2 data streams.Firstly,it used the 3σrules as an adaptive threshold to realize the outlier detection;Secondly,extracted the average of detecting sliding window as its characteristic value,and then built a spa-tial-temporal matrix between neighbor nodes in specified interval,analyzed the spatial-temporal correlation of adjacent nodes characteristic value based on fuzzy clustering,and classified the results.The algorithm could identify the abnormal leakage probability according to the results of the classification.Finally,this paper evaluated the algorithm by real observation data, and analyzed the selection of parameters.The results show that the proposed algorithm can recognize the anomaly caused by leakage,and has higher detection rate and lower false rate.关键词
模糊聚类/时空异常/CO2/数据流Key words
fuzzy cluster/spatial-temporal anomaly/CO2/data streams分类
信息技术与安全科学引用本文复制引用
刘莘,张赛男..基于模糊聚类的 CO2数据流时空异常模式的研究[J].计算机应用研究,2016,33(8):2353-2357,5.基金项目
“十二五”科技支撑计划项目（2011BAC08B03）；江苏高校优势学科建设工程资助项目 （）
