A novel water quality data analysis framework based on time-series data mining

doi:10.1016/j.jenvman.2017.03.024

	A novel water quality data analysis framework based on time-series data mining
	Deng, Weihui 1,2; Wang, Guoyin 1
刊名	JOURNAL OF ENVIRONMENTAL MANAGEMENT
	2017-07-01
卷号	196 页码:365-375
关键词	Time-series data mining Cloud model Water quality analysis Similarity measure Anomaly detection Pattern discovery
ISSN号	0301-4797
DOI	10.1016/j.jenvman.2017.03.024
通讯作者	Wang, GY (reprint author), Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, 266 Fangzheng Ave,Shuitu Hi Tech Ind Pk, Chongqing 400714, Peoples R China.
英文摘要	The rapid development of time-series data mining provides an emerging method for water resource management research. In this paper, based on the time-series data mining methodology, we propose a novel and general analysis framework for water quality time-series data. It consists of two parts: implementation components and common tasks of time-series data mining in water quality data. In the first part, we propose to granulate the time series into several two-dimensional normal clouds and calculate the similarities in the granulated level. On the basis of the similarity matrix, the similarity search, anomaly detection, and pattern discovery tasks in the water quality time-series instance dataset can be easily implemented in the second part. We present a case study of this analysis framework on weekly Dissolve Oxygen time-series data collected from five monitoring stations on the upper reaches of Yangtze River, China. It discovered the relationship of water quality in the mainstream and tributary as well as the main changing patterns of DO. The experimental results show that the proposed analysis framework is a feasible and efficient method to mine the hidden and valuable knowledge from water quality historical time-series data. (C) 2017 Elsevier Ltd. All rights reserved.
资助项目	National Science and Technology Major Project[2014ZX07104-006] ; National Natural Science Foundation of China[61572091]
WOS研究方向	Environmental Sciences & Ecology
语种	英语
出版者	ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
WOS记录号	WOS:000401888300036
内容类型	期刊论文
源URL	[http://172.16.51.4:88/handle/2HOD01W0/200]
专题	中国科学院重庆绿色智能技术研究院
通讯作者	Wang, Guoyin
作者单位	1.Chinese Acad Sci, Chongqing Key Lab Big Data & Intelligent Comp, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Deng, Weihui,Wang, Guoyin. A novel water quality data analysis framework based on time-series data mining[J]. JOURNAL OF ENVIRONMENTAL MANAGEMENT,2017,196:365-375.
APA	Deng, Weihui,&Wang, Guoyin.(2017).A novel water quality data analysis framework based on time-series data mining.JOURNAL OF ENVIRONMENTAL MANAGEMENT,196,365-375.
MLA	Deng, Weihui,et al."A novel water quality data analysis framework based on time-series data mining".JOURNAL OF ENVIRONMENTAL MANAGEMENT 196(2017):365-375.