Fuzzy GML Modeling Based on Vague Soft Sets

Fuzzy GML Modeling Based on Vague Soft Sets
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基于Vague软集的模糊GML建模

DOI:
10.3390/ijgi6010010
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发表时间:
2017-01
影响因子:
3.4
通讯作者:
邹瑶
邹瑶
中科院分区:
地球科学3区
文献类型:
--
作者:
韦波;解青青;孟媛媛;邹瑶

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开放地理空间联盟(OGC)地理标记语言(GML)以文本模式显式表示地理空间知识。在空间知识表达中不可避免地会遇到各种模糊问题。特别是对于那些文本模式的表情,这种模糊性会更广泛。用GML描述和表示模糊性似乎是必要的。GML中存在三种类型的模糊性:元素模糊性、链模糊性和属性模糊性。元素模糊性和链模糊性都是GML元素间模糊性的反映,因此可以用GML中元素模糊性的表示来代替链模糊性的表示。在Vague软集理论的基础上,针对GML文档类型定义(DTD)和GML模式下的模糊建模,分别提出了两种建模方法:DTD建模和GML模式建模。引入了与模糊软集相关的五个元素或对。然后,根据它们不同的链和不同的模糊数据类型,设计并给出了相应的DTD和五元模式。引入5个元素或对是模糊软集GML建模的基础,而相应的DTD和模式修改是实现建模的关键。模糊软集GML的建立使GML能够表示模糊性,解决了GML缺乏模糊信息表达的问题。
The Open Geospatial Consortium (OGC) Geography Markup Language (GML) explicitly represents geographical spatial knowledge in text mode. All kinds of fuzzy problems will inevitably be encountered in spatial knowledge expression. Especially for those expressions in text mode, this fuzziness will be broader. Describing and representing fuzziness in GML seems necessary. Three kinds of fuzziness in GML can be found: element fuzziness, chain fuzziness, and attribute fuzziness. Both element fuzziness and chain fuzziness belong to the reflection of the fuzziness between GML elements and, then, the representation of chain fuzziness can be replaced by the representation of element fuzziness in GML. On the basis of vague soft set theory, two kinds of modeling, vague soft set GML Document Type Definition (DTD) modeling and vague soft set GML schema modeling, are proposed for fuzzy modeling in GML DTD and GML schema, respectively. Five elements or pairs, associated with vague soft sets, are introduced. Then, the DTDs and the schemas of the five elements are correspondingly designed and presented according to their different chains and different fuzzy data types. While the introduction of the five elements or pairs is the basis of vague soft set GML modeling, the corresponding DTD and schema modifications are key for implementation of modeling. The establishment of vague soft set GML enables GML to represent fuzziness and solves the problem of lack of fuzzy information expression in GML.
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