Generalized Euler-Venn Diagrams for Fuzzy Sets

Yu. V. Mironova
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引用次数: 3

Abstract

The fuzzy set concept is often used in solution of problems in which the initial data is difficult or impossible to represent in the form of specific numbers or sets. Geo-information objects are distinguished by their uncertainty, their characteristics are often vague and have some error. Therefore, in the study of such objects is introduced the concept of "fuzziness" — fuzzy sets, fuzzy logic, linguistic variables, etc. The fuzzy set concept is given in the form of membership function. An ordinary set is a special case of a fuzzy one. If we consider a fuzzy object on the map, for example, a lake that changes its shape depending on the time of year, we can build up for it a characteristic function from two variables (the object’s points coordinates) and put a certain number in accordance with each point of the object. That is, we can describe a fuzzy set using its two-dimensional graphical image. Thus, we obtain an approximate view of a surface z = μ(x, y) in three-dimensional space. Let us now draw planes parallel to the plane. We’ll obtain intersections of our surface with these planes at 0 ≤ z ≤ 1. Let's call them as isolines. By projecting these isolines on the OXY plane, we’ll obtain an image of our fuzzy set with an indication of intermediate values μ(x, y) linked to the set’s points coordinates. So we’ll construct generalized Euler — Venn diagrams which are a generalization of well-known Euler — Venn diagrams for ordinary sets. Let's consider representations of operations on fuzzy sets A a n d B. Th e y u s u a l l y t a k e : μA B = min (μA,μB ), μA B = max (μA,μB ), μA = 1 − μA. Algebraic operations on fuzzy sets are defined as follows: μ A B x μ A x μ B x ( ) = ( ) + ( ) − −μ A (x)μ B (x), μ A B x μ A x μ B x ( ) = ( ) ( ), μ A (x) = 1 − μ A (x). Let's construct for a particular problem a generalized Euler — Venn diagram corresponding to it, and solve subtasks graphically, using operations on fuzzy sets, operations of intersection and integrating of the diagram’s bars.
模糊集的广义欧拉-维恩图
模糊集概念通常用于解决初始数据难以或不可能以特定数字或集合的形式表示的问题。地理信息对象具有不确定性,其特征往往是模糊的,存在一定的误差。因此,在对这类对象的研究中引入了“模糊性”的概念——模糊集、模糊逻辑、语言变量等。模糊集的概念以隶属函数的形式给出。普通集合是模糊集合的一种特殊情况。如果我们考虑地图上的一个模糊物体,例如,一个湖泊的形状会随着一年中的时间而改变,我们可以为它建立一个由两个变量(物体的点坐标)组成的特征函数,并根据物体的每个点设置一个特定的数字。也就是说,我们可以用一个模糊集的二维图形图像来描述它。因此,我们得到了三维空间中曲面z = μ(x, y)的近似视图。现在我们画一些平行于平面的平面。我们将得到曲面与这些平面在0≤z≤1处的交点。我们称它们为等值线。通过在OXY平面上投影这些等值线,我们将得到模糊集的图像,并指示中间值μ(x, y)与集合的点坐标相关联。所以我们要构造广义欧拉-维恩图它是对普通集合的著名欧拉-维恩图的推广。让我们考虑模糊集A A n和B上操作的表示。其中,μA B = min (μA,μB), μA B = max (μA,μB), μA = 1−μA。对模糊集代数操作定义如下:μA B xμμB x ( ) = ( ) + ( ) −−μA (x)μB (x),μA B xμμB x ( ) = ( ) ( ), μ(x) = 1−μ(x)。让我们为一个特殊的问题构造一个广义欧拉-维恩图对应,并解决子任务图形,使用模糊集上的操作,操作图的交叉和集成的酒吧。
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