Mining time-series association rules from Western Pacific spatial-temporal data

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Ma, Weixuan^1,2 ; Xue, Cunjin^1 ; Zhou, Junqi^2

Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No.9 Dengzhuang South Road Haidian District, Beijing, 100094, China^1

Wuhan University, Luojia Hill, Wuchang District, Wuhan 430072, Hubei, China^2

关键词: Concept generalization;    Environmental problems;    Improved apriori algorithms;    Qualitative attributes;    Quantitative attributes;    Spatial-temporal data;    Spatial-temporal data minings;    Time-series association rules;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012224/pdf
DOI  :  10.1088/1755-1315/17/1/012224

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

With increasing concerns about the environmental problem as well as tremendous environmental issues impacting on our daily life, a new requirement for analysis of environmental changes and effect has been proposed. In this paper we use Western Pacific events and basic background database as its data source to find the association between different marine parameters. The improved Apriori algorithm is utilized to discover knowledge in magnanimous spatio-temporal data. There are two main steps. First is according to the different variation degree of each point, the study area can be divided into lots of spatial-temporal transaction zones. Second is use the improved Apriori algorithm for spatial-temporal data mining. For the need of mining algorithm, the quantitative attributes need to be transformed into qualitative attributes. The concept generalization method is utilized to divide the original attribute data into several levels. Then the Apriori algorithm can be used to discover the potential association between marine parameters within the given time frame.