基于位置不确定性的多尺度空间方向关系相似性粗集模型

Rough-set Model of the Similarity of Multi-scale Space Direction Relations Based on Positional Uncertainty

  • 摘要: 针对现有研究中没有考虑空间目标的不确定性对空间方向关系相似性的影响问题,借助粗集表达不确定性问题的优势,定义在空间方向关系锥形模型中空间方向关系的粗集表达方法,以此为基础提出基于空间对象位置不确定性的多尺度空间方向关系相似性的计算和粗集表达方法,使得多尺度空间方向关系相似性的取值在一个区间范围内变动,在多尺度空间方向关系相似性概念表达上更符合人类的认知逻辑

     

    Abstract: In order to resolve the disadvantage that similarity models of space direction relations do not consider the uncertainty of space target, by means of the advantage that rough-set expresses uncertainty problems, rough-set expression method of space direction relations is defined in cone-shaped models of cardinal direction relations.The computation and rough-set expression method of similarity of multi-scale space direction relations based on the positional uncertainty of space target are proposed, this method makes that the value of similarity of multi-scale space direction relations is varied in a interval, which accorded with human cognition of similarity of multi-scale space direction relations

     

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