一种基于事件的海洋关联规则挖掘方法

doi:10.3969/j.issn.0255-8297.2016.04.004

应用科学学报 ›› 2016, Vol. 34 ›› Issue (4): 387-396.doi: 10.3969/j.issn.0255-8297.2016.04.004

一种基于事件的海洋关联规则挖掘方法

李溢龙^1,2, 李晓红¹, 薛存金^1,3, 林孝松²

1. 中国科学院遥感与数字地球研究所数字地球重点实验室, 北京 100094;
2. 重庆交通大学建筑与城市规划学院, 重庆 400074;
3. 海南省地球观测重点实验室, 三亚 572029

收稿日期:2015-10-13 修回日期:2016-03-22 出版日期:2016-07-30 发布日期:2016-07-30
通信作者: 薛存金,博士,副研究员,研究方向:海洋地理信息系统、海洋时空分析方法,E-mail:xuecj@radi.ac.cn E-mail:xuecj@radi.ac.cn
基金资助:
国家自然科学基金（No.41371385）；中国科学院青年促进会项目基金（No.2013113）资助

Marine Association Rule Mining Based on Events

LI Yi-long^1,2, LI Xiao-hong¹, XUE Cun-jin^1,3, LIN Xiao-song²

1. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China;
2. College of Architecture and Urban Planning, Chongqing Jiaotong University, Chongqing 400074, China;
3. Key Laboratory of the Earth Observation, Sanya 572029, Hainan Province, China

Received:2015-10-13 Revised:2016-03-22 Online:2016-07-30 Published:2016-07-30

摘要/Abstract

摘要：

在Apriori算法的递归链接-剪枝概念上，设计了面向海洋异常事件的关联规则挖掘算法.首先给出事件的相关概念与定义、事件的规则表达及评价指标.根据事件的定义和支持度阈值，生成事件频繁1-项集，并设计面向事件的链接-剪枝算法，实现频繁k-项集到(k+1)-项集的产生.根据事件强关联规则评价指标，提取海洋事件强关联规则.通过太平洋海洋异常事件的关联规则挖掘和典型异常事件间的关联规则分析，验证了该方法的正确性和可行性.

关键词: 关联规则, 太平洋, 海洋异常事件, 事件挖掘算法

Abstract:

An association rule mining algorithm is designed for anomalous oceanic events based on recursive "link-prune" of a priori algorithm. Concepts, definitions, rule expression and evaluation indicator related to events are introduced first. Based on a threshold of support and definition of event, event frequent 1-item set and designed an event-oriented link-prune algorithm is generated for frequent (k + 1)-item set from frequent k-item set. Marine events' strong association rule is then extracted based on events' strong association rule evaluation indicator. A case study on the association rule mining of Pacific marine abnormal events and association rule analysis on typical abnormal events are used to show correctness and feasibility of the proposed method.

Key words: association rule, the PacificOcean, marine abnormal event, event mining algorithm

中图分类号:

TP79

李溢龙, 李晓红, 薛存金, 林孝松. 一种基于事件的海洋关联规则挖掘方法[J]. 应用科学学报, 2016, 34(4): 387-396.

LI Yi-long, LI Xiao-hong, XUE Cun-jin, LIN Xiao-song. Marine Association Rule Mining Based on Events[J]. Journal of Applied Sciences, 2016, 34(4): 387-396.

参考文献

[1] Mcphaden M J, Zebiak S E, Glantz M H. ENSO as an integrating concept in earth science[J]. Science, 2006, 314(5806): 1740-1745.
[2] Xue C J, Dong Q, Qin L J. A cluster-based method for marine sensitive object extraction and representation[J]. Journal of Ocean University of China, 2015, 14(4): 612-620.
[3] Agrawal R, Srikant R. Fast algorithms for mining association rules [C]//Proceedings of International Conference on Very Large Databases (VLDB). 1994, 1215: 487-499.
[4] 李光强, 邓敏, 张纬玲, 陈翼. 利用事件影响域挖掘时空关联规则[J]. 遥感学报, 2010, 14(3): 468-481. Li G Q, Deng M, Zhang W L, Chen Y. Events-coverage based spatio-temporal association rules mining method [J]. Journal of Remote Sensing, 2010, 14(3): 468-481. (in Chinese)
[5] Wu T S, Song G J, Ma X J, Xie K Q, Gao X P, Jin X X. Mining geographic episode association patterns of abnormal events in global earth science data [J]. Science in China Series E: Technological Sciences, 2008, 51(1): 155-164.
[6] Huang Y, Zhang L Q, Zhang P S. A framework for mining sequential patterns from spatiotemporal event data sets [J]. IEEE Transactions on Knowledge and Data Engineering, 2008, 20(4): 433-448.
[7] 柴思跃, 苏奋振, 周成虎. 基于周期表的时空关联规则挖掘方法与实验[J]. 地球信息科学学报, 2011, 13(4): 455-462. Chai S Y, Su F Z, Zhou C H. Period table based spatio-temporal association rules mining[J]. Journal of Geo-information Science, 2011, 13(4): 455-462. (in Chinese)
[8] Saulquin B, Fablet R, Mercier G, Demarcq H, Mangin A, d'Andon O H F. Multiscale event-based mining in geophysical time series: characterization and distribution of significant time-scales in the sea surface temperature anomalies telatively to ENSO periods from 1985 to 2009 [J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(8): 3543-3552.
[9] Xue C J, Dong Q, Li X H, Fan X, Li Y L, Wu S C. A remote sensing driven system for mining marine spatial temporal association patterns [J]. Remote Sensing, 2015, 7(7): 9149-9165.
[10] Byna S, Wehner M F, Wu K J. Detecting atmospheric rivers in large climate datasets[C]//Proceedings of the 2nd International Workshop on Petascal Data Analytics: Challenges and Opportunities. ACM, 2011: 7-14.
[11] Chen G, Ma J, Fang C, Han Y. Global oceanic precipitation derived from TOPEX and TMR: climatology and variability [J]. Journal of Climate, 2003, 16(23): 3888-3904.
[12] Xue C J, Song W J, Qin L J. A spatiotemporal mining framework for abnormal association patterns in marine environments with a time series of remote sensing images [J]. International Journal of Applied Earth Observation and Geo-information, 2015, 38: 105-114.
[13] Xue C J, Dong Q, Fan X. Spatio temporal association patterns of multiple parameters in the northwestern Pacific Ocean and their relationships with ENSO [J]. International Journal of Remote Sensing, 2014, 35(11/12): 4467-4483.
[14] Hou X Y, Dong Q, Xue C J, Song W J, Qin L J, Fan X. Seasonal evolution of the interannual variability of chlorophyll-a concentration and its forcing factors in the northwestern Pacific from 1998 to 2010 [J]. International Journal of Remote Sensing, 2014, 35(11/12): 4138-4155.
[15] 李晓燕, 翟盘茂. ENSO 事件指数与指标研究[J]. 气象学报, 2000, 58(1): 102-109. Li X Y, Zhai P M. On indices and indicators of ENSO episodes [J]. Act Meteorologica Sinica, 2000, 58(1): 102-109. (in Chinese)
[16] Wilson C, Adamec D. Correlations between surface chlorophyll and sea surface height in the tropical Pacific during the 1997-1999 El Nineo-southern oscillation event [J]. Journal of Geophysical Research, 2001, 106: 31175-31188.

一种基于事件的海洋关联规则挖掘方法

Marine Association Rule Mining Based on Events

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 7

编辑推荐

Metrics

本文评价

[1]	黄俊杰, 谭波, 陈孝明, 陈江平, 阮羚, 冯莞舒, 熊宇. 用Apriori关联规则挖掘算法发现湖北电网雷击灾害的时空分布规律[J]. 应用科学学报, 2017, 35(1): 31-41.
[2]	陈江平, 谭波, 连世忠. 湖北省雷击关联规则挖掘发现[J]. 应用科学学报, 2017, 35(1): 42-50.
[3]	姜静逸1，韩松臣1，汤新民1，倪金霞1，崔国山2. 基于满意度控制的机场应急救援决策规则的数据挖掘[J]. 应用科学学报, 2009, 27(6): 644-650.
[4]	朱玉全, 杨鹤标. 负关联规则挖掘算法研究[J]. 应用科学学报, 2006, 24(4): 382-386.
[5]	陆介平;倪巍伟;孙志挥. 基于关联分析的高维空间异常点发现 [J]. 应用科学学报, 2006, 24(1): 60-0060 .
[6]	陈耿;朱玉全;宋余庆;陆介平;孙志挥. 基于频繁模式树的约束最大频繁项目集挖掘算法研究 [J]. 应用科学学报, 2006, 24(1): 64-0064 .
[7]	刘耀和, 胡宝清. 模糊关联规则及其挖掘算法[J]. 应用科学学报, 2003, 21(4): 373-376.