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粗糙集作为一种处理不确定性问题的工具,近年来在GIS中得到了广泛的应用。它利用上、下近似来逼近对象。在以往的GIS粗糙集应用中,都是基于等价划分的pawlark粗糙集。本文基于划分之中可以存在交集的覆盖粗糙集,利用近年在基础数学研究中的一些覆盖粗糙集的理论与性质,探讨了GIS不确定研究的覆盖近似空间、覆盖粗糙集、模糊覆盖粗糙集、模糊覆盖粗糙隶属函数等。发现覆盖粗糙集在处理GIS不确定性问题时,有比粗糙集更广的适应范围。
As a tool to deal with the problem of uncertainty, rough set has been widely used in GIS in recent years. It uses the upper and lower approximation to approximate the object. In the past GIS rough set applications, are based on the equivalent partition pawlark rough set. In this paper, based on the existence of intersection rough sets and the theory and properties of some cover rough sets in basic mathematics research in recent years, this paper discusses the coverage approximate space, covering rough set, fuzzy covering rough set, Fuzzy coverage, membership function and so on. Finding Coverage Rough Sets There is a broader range of adaptation than rough sets in dealing with GIS uncertainty.