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提出了一个基于粒计算的制图综合选取知识获取模型,旨在探讨从范例数据中获取制图对象之间内在关联知识的途径,为制图综合选取推理提供决策规则。并以河流选取为例,对基于粒计算的制图综合选取的知识获取模型和方法进行了讨论。
A model of knowledge acquisition of cartographic comprehensive selection based on grain computing is proposed. The purpose of this paper is to explore the ways of obtaining the inherent related knowledge among cartographic objects from the example data and to provide decision rules for cartographic comprehensive reasoning. Taking the example of river selection as an example, the model and method of knowledge acquisition based on grain calculation for comprehensive selection of cartography are discussed.