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  • 标题:Variable precision rough set model for attribute selection on environment impact dataset
  • 本地全文:下载
  • 作者:Ani Apriani ; Iwan Tri Riyadi Yanto ; Septiana Fathurrohmah
  • 期刊名称:IJAIN (International Journal of Advances in Intelligent Informatics)
  • 印刷版ISSN:2442-6571
  • 电子版ISSN:2548-3161
  • 出版年度:2018
  • 卷号:4
  • 期号:1
  • 页码:70-75
  • DOI:10.26555/ijain.v4i1.109
  • 语种:English
  • 出版社:Universitas Ahmad Dahlan
  • 摘要:The investigation of environment impact have important role to development of a city. The application of the artificial intelligence in form of computational models can be used to analyze the data. One of them is rough set theory. The utilization of data clustering method, which is a part of rough set theory, could provide a meaningful contribution on the decision making process. The application of this method could come in term of selecting the attribute of environment impact. This paper examine the application of variable precision rough set model for selecting attribute of environment impact. This mean of minimum error classification based approach is applied to a survey dataset by utilizing variable precision of attributes. This paper demonstrates the utilization of variable precision rough set model to select the most important impact of regional development. Based on the experiment, The availability of public open space, social organization and culture, migration and rate of employment are selected as a dominant attributes. It can be contributed on the policy design process, in term of formulating a proper intervention for enhancing the quality of social environment.
  • 关键词:Environment;VPRS;Error classification;Attribute selection
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