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基于Rough Set的空间数据分类方法
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本文研究得到国家863高科技项目基金(No.863-306-ZD-07-4)资助.

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    摘要:

    近来,数据采掘的研究已从关系型和事务型数据库扩展到空间数据库.空间数据采掘是一个很有发展前景的领域,其中空间数据分类的研究尚处在起步阶段.该文分析和比较了现有的几个空间数据分类方法的利和弊,提出利用Rough Set的三阶段空间分类过程.实验结果表明,该算法对于解决包含不完整空间信息的问题是有效的.

    Abstract:

    Recent studies have extended the scope of data mining from relational and transactional databases to spatial databases. Spatial data mining is a promising field, where the research work on spatial data classification is still in its initial stage. In this paper, the advantages and the disadvantages of several existing methods of spatial data classification are compared first. Then an effective three-step method, which is based on the rough set theory for spatial data classification, is proposed. The validity of this algorithm to the problem of incomplete spatial information is verified by pertinent experimental results.

    参考文献
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石云,孙玉芳,左春.基于Rough Set的空间数据分类方法.软件学报,2000,11(5):673-678

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  • 收稿日期:1999-02-04
  • 最后修改日期:1999-05-24
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