{"title":"模糊区域和空间关系:粗糙集方法","authors":"T. Beaubouf, F. Petry","doi":"10.1109/ICCIMA.2001.970485","DOIUrl":null,"url":null,"abstract":"Uncertainty management is necessary for spatial data and GIS applications. This paper focuses on topological relationships and uncertainty in spatial data regions. We discuss the representation of vague regions using the RCC-8 theory and show how rough sets can improve on this methodology through the use of its indiscernibility relation and approximation regions.","PeriodicalId":232504,"journal":{"name":"Proceedings Fourth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2001","volume":"167 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Vague regions and spatial relationships: a rough set approach\",\"authors\":\"T. Beaubouf, F. Petry\",\"doi\":\"10.1109/ICCIMA.2001.970485\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Uncertainty management is necessary for spatial data and GIS applications. This paper focuses on topological relationships and uncertainty in spatial data regions. We discuss the representation of vague regions using the RCC-8 theory and show how rough sets can improve on this methodology through the use of its indiscernibility relation and approximation regions.\",\"PeriodicalId\":232504,\"journal\":{\"name\":\"Proceedings Fourth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2001\",\"volume\":\"167 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Fourth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2001\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIMA.2001.970485\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Fourth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2001","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIMA.2001.970485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vague regions and spatial relationships: a rough set approach
Uncertainty management is necessary for spatial data and GIS applications. This paper focuses on topological relationships and uncertainty in spatial data regions. We discuss the representation of vague regions using the RCC-8 theory and show how rough sets can improve on this methodology through the use of its indiscernibility relation and approximation regions.
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