计算机科学 ›› 2013, Vol. 40 ›› Issue (11): 276-279.

• 人工智能 • 上一篇    下一篇

基于粒隶属约简的地震数据库简化方法研究

孙昱薇,郑学锋,潘常周,靳平   

  1. 西北核技术研究所 西安710024;西北核技术研究所 西安710024;西北核技术研究所 西安710024;西北核技术研究所 西安710024
  • 出版日期:2018-11-16 发布日期:2018-11-16

Research on Simplification Methods of Seismic Database for CTBT Based on Granular Membership Reduction

SUN Yu-wei,ZHENG Xue-feng,PAN Chang-zhou and JIN Ping   

  • Online:2018-11-16 Published:2018-11-16

摘要: 地震数据的共享大大推动了地震科学的研究进展,对海量地震数据进行知识发现,以促进地震监测技术发展。概念格是知识发现的有力工具,知识约简是知识发现的一个重要方面。通过定义的隶属关系对形式背景进行分类,利用粒隶属约简对隶属类做有选择的简化;并提出简化概念格扩充定理,最终将简化概念扩充为原形式背景概念格。对UCI机器学习知识库真实数据集进行了实验,结果表明该方法可行有效,可最大限度地简化对象属性。该方法正应用于地震核查数据库。

关键词: 地震数据,概念格,形式背景,粒隶属约简

Abstract: Sharing of seismic data greatly promote the progress of seismic science.Meanwhile,knowledge discovery for massive seismic data is advancing the development of seismic monitoring technology.Concept lattice is a powerful tool in knowledge discovery.Knowledge reduction,moreover,is one of the important aspects of knowledge discovery.Firstly,this paper used membership relationships defined to classify formal context,and simplified membership class by using granular membership reduction.And then,the reduced concept lattice was expanded by selecting objects and attributes dynamically,accordingly,the concept lattice of original formal context was converted eventually.Finally,typical examples of UCI database were analyzed.The results show that this method is effective and can simplify the objects and attributes in the maximum scale.The method is also applyied in the seismic database.

Key words: Seismic data,Concept lattice,Formal context,Granular membership reduction

[1] 库尔哈奈克.地震图解析[M].刘启元,吴宁远,修济刚,译.北京:地震出版社,1990:10-40
[2] 郑学锋,靳平,张慧民,等.禁核试核查中的信息知识库系统[A]∥中国地球物理会第二十七届年会论文集[C].中国地球物理2011,2011:507
[3] 周克昌.分布式地震数据库系统的研究与实践[D].北京:中国地震局物理研究所,2003
[4] 王洪伟.基于GIS的地震数据库结构设计及其访问技术研究[D].青岛:中国海洋大学,2008
[5] Wille R.Restructuring lattice theory:an approach based on hierarchies of concepts[M]∥Rival I,ed.Ordered Sets.Reidel:Dordrecht-Boston,1982:445-470
[6] Ganter B,Wille R.Formal Concept Analysis:MathematicalFoundations[M].New York:Springer-Verlag,1999
[7] Ho T B.An approach to concept formation based on formalconcept analysis[J].IEICE Trans.Information and Systems,1995,E78-D(5):553-559
[8] Zhang Wen,Xiu Wei-ling,Qi Jian-jun.Attribute reduction theory and approach to concept analysis[J].Proceedings of the 10th International Conference on Rough Sets,Data Mining,and Granular Computing,2005,48(6):713-726
[9] 魏玲,祁建军,张文修.概念格与粗糙集的关系研究[J].计算机科学,2006,33(3):19-21
[10] 王霞,张文修.概念格的属性约简与属性特征[J].计算机工程与应用,2008,4(12):1-4
[11] 吴克生,魏玲.基于区间值形式背景的属性约简[Z].信息科学与技术中心论坛,2010:4978-4981
[12] 黄艳,任苗苗,魏玲.区间值决策形式背景的属性值向量约简[J].计算机科学,2012,39(1):193-197
[13] 杨丽,徐扬.基于形式背景的概念格约简及其修复[J].计算机工程,2008,34(9):22-24

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