Transitivity-preserving fuzzification schemes for cardinality-based similarity measures

A family of fuzzification schemes is proposed that can be used to transform cardinality-based similarity measures for ordinary sets into similarity measures for fuzzy sets in a finite universe. The family is based on rules for fuzzy set cardinality and for the standard operations on fuzzy sets. In particular, the fuzzy set intersections are pointwisely generated by Frank t-norms. The fuzzification schemes are applied to a variety of previously studied rational cardinality-based similarity measures for ordinary sets and it is demonstrated that transitivity is preserved in the fuzzification process.     

On the transitivity of a parametric family of cardinality-based similarity measures

We introduce a parametric family of cardinality-based similarity measures for ordinary sets (on a finite universe) harbouring numerous well-known similarity measures. We characterize the ?ukasiewicz-transitive and product-transitive members of this family. Their importance derives from their one-to-one correspondence with pseudo-metrics. Fuzzification schemes based on a commutative quasi-copula are then used to transform these similarity measures for ordinary sets into similarity measures for fuzzy sets, rendering them applicable on graded feature set representations of objects. The main result of this paper is that transitivity, and hence also the corresponding dual metric interpretation, is preserved along this fuzzification process.     

Fuzzy partitions and relations; an axiomatic basis for clustering

In this paper some connections between fuzzy partitions and similarity relations are explored. A new definition of transitivity for fuzzy relations yields a relation-theoretic characterization of the class of all psuedo-metrics on a fixed (finite) data set into the closed unit interval. This notion of transitivity also links the triangle inequality to convex decompositions of fuzzy similarity relations in a manner which may generate new techniques for fuzzy clustering. Finally, we show that every fuzzy c-partition of a finite data set induces a psuedo-metric of the type described above on the data.     

二级传递性与二级传递模糊矩阵

推广传递性概念,给出二级传递性的定义;研究二级传递模糊矩阵的性质,给出其若干等价刻画;证明二级传递模糊矩阵或者收敛或者周期为2,指数不大于n 1;讨论二级传递与强传递、k-传递和泛传递等概念之间的关系,指出二级传递是传递性概念的一种新的推广形式。     

Proximity relations in the fuzzy relational database model

The fuzzy relational model of Buckles and Petry is a rigorous scheme for incorporating non-ideal or fuzzy information in a relational database. In addition to providing a consistent scheme for representing fuzzy information in the relational structure, the model possesses two critical properties that hold for classical relational databases. These properties are that no two tuples have identical interpretations and each relational operation has a unique result.The fuzzy relational model relies on similarity relations for each scalar domain in the fuzzy database. These relations are reflexive, symmetric, and max-min transitive. In addition to introducing fuzziness into the relational model, each similarity relation induces equivalence classes in its domain. It is the existence of these equivalence classes that provides the model with the important properties possessed by classical relational databases.In this paper, we extend the fuzzy relational database model of Buckles and Petry to deal with proximity relations for scalar domains. Since reflexivity and symmetry are the only constraints placed on proximity relations, they generalize the notion of similarity relations. We show that it is possible to induce equivalence classes from proximity relations; thus, the ‘nice’ properties of the fuzzy relational model of Buckles and Petry are preserved. Furthermore, the removal of the max-min transitivity restriction also provides database users with more freedom to express their value structures.     

Similarity,inclusion and entropy measures between type-2 fuzzy sets based on the Sugeno integral

Similarity measures of type-2 fuzzy sets are used to indicate the similarity degree between type-2 fuzzy sets. Inclusion measures for type-2 fuzzy sets are the degrees to which a type-2 fuzzy set is a subset of another type-2 fuzzy set. The entropy of type-2 fuzzy sets is the measure of fuzziness between type-2 fuzzy sets. Although several similarity, inclusion and entropy measures for type-2 fuzzy sets have been proposed in the literatures, no one has considered the use of the Sugeno integral to define those for type-2 fuzzy sets. In this paper, new similarity, inclusion and entropy measure formulas between type-2 fuzzy sets based on the Sugeno integral are proposed. Several examples are used to present the calculation and to compare these proposed measures with several existing methods for type-2 fuzzy sets. Numerical results show that the proposed measures are more reasonable than existing measures. On the other hand, measuring the similarity between type-2 fuzzy sets is important in clustering for type-2 fuzzy data. We finally use the proposed similarity measure with a robust clustering method for clustering the patterns of type-2 fuzzy sets.     

Behavior in Repeated Prisoner's Dilemma Games with Shifted Outcomes Analyzed with a Statistical Learning Model

A fuzzy set theoretical framework is proposed for the analysis of sociometric structure characterized by vagueness of liking between individuals and a person's relative degree of belonging to a social group. Max‐min transitivity of a fuzzy relation is employed as a basic concept to examine the degree of liking and clustering in group structures. A distance model based on min‐max transitivity is also formulated as a special case of transitivity analysis. Other notions of transitivity such as the max‐product and the max‐* are also discussed. An empirical analysis is performed to examine the applicability of the proposed transitivity concepts. It appears that the current methodological construct provides a more appropriate perspective in the analysis of the group structure properties.     

广义模糊传递性和形式三传递模糊矩阵

提出广义模糊传递性和形式三传递阵的概念，给出已有模糊传递定义的一种统一形式，确定所有的三传递模糊矩阵，初步理清它们的层次和部分等价关系，为模糊矩阵传递性进一步研究和应用提供背景和方法。     

关于粗糙模糊集的相似度量

基于对不确定性信息处理的背景,定义了粗糙模糊值与粗糙模糊集的相似度量,研究了它们的有关性质.     

关于模糊严格偏好关系的传递性

给定一个模糊关系,Ovchinnikov和Roubens引进了非常一般的模糊严格偏好关系定义,本文将详细讨论该偏好关系的弱传递性,一致性,强传递性以及非循环性等传递性有关的性质。     

On the enumeration of distinct fuzzy switching functions

This paper entails the development of bound equations on the number of minimized fuzzy switching functions. A triangular matrix representing the transitivity between fundamental fuzzy phrases is discussed and applied in the enumeration process. Improved upper and lower bounds have been developed by use of the transitivity matrix. In addition, an algorithm is described to calculate the number of distinct fuzzy switching functions for any number of variables.     

An interactive dynamic programming approach to multicriteria discrete programming

Several interactive schemes for solving multicriteria discrete programming problems are developed under a dynamic programming framework. It is assumed that the decision maker's preference structure satisfies the conditions of transitivity, monotonicity, and nonsatiation. Hybrid procedures are also structured by including branch and bound ideas into the recursions. Initial computational results are offered.     

基于Type-2模糊贴近度在生态上的应用

分析比较了Type-1模糊贴近度与Type-2贴近度的特点,并将Type-2模糊贴近度的概念和相应运算应用到生态系统中,给出了物种动态的生态位模型,计算了物种实际生态位与理想生态位的重叠,根据重叠的精确值和区间值分别研究了物种进化的动态行为和进化程度.     

基于偏序集的模糊互补矩阵次序一致性检验与调整

针对模糊互补矩阵次序一致性检验和调整存在争议和繁杂问题,提出了模糊互补矩阵次序一致性检验与调整的偏序集表示方法。在定义了偏序集、模糊互补矩阵、截集矩阵等相关概念基础上,求出模糊互补矩阵B的0.5水平截集矩阵,证明了模糊互补判断矩阵次序一致性和0.5水平截集矩阵为偏序关系矩阵的等价性;模糊互补判断矩阵完全次序一致性的充要条件是任意截集均满足传递性;任意截集满足传递性和偏序关系矩阵的等价性。结果表明,利用0.5水平截集矩阵转换为矩阵来检验模糊互补矩阵的次序一致性;通过调整每个截集矩阵满足传递性并赋值,能够达到模糊互补矩阵完全次序一致性。最后,通过两个算例验证该检验和调整方法的合理性和可行性。     

Some dissenting views on the transitivity of individual preference

(1) The transitivity property is not a necessary condition for the rationality of all individual preference relations. (2) A weakened definition of the transitivity is not necessarily relevant. (3) The non-transitivity of fuzzy preference relations is not inconsistent with a fuzzy total preorder structure on the set of alternatives.Deceased.     

基于粗糙模糊集的聚类决策及应用

对基于粗糙模糊集的聚类问题进行了研究.首先,定义了粗糙模糊值与粗糙模糊集的相似度,给出了粗糙模糊集相似度的一般表达式;然后利用该公式构建了模糊相似矩阵,进而给出了粗糙模糊集的一种聚类方法;最后以实际算例说明了这种思想.     

Fuzzy Transitive Relations

A modified definition of fuzzy transitivity is given.Several properties of this new definition are obtained.Effect of these new properties of transitivity on equivalence relations is also studied.     

直觉模糊度量空间上的半群作用

讨论在直觉模糊度量空间上的拓扑半群作用,引入诸如拓扑传递性,点传递性及点稠传递性等概念.考虑非敏感性与传递性,等度连续等动力学性质的相互关系.     

Aggregation of monotone reciprocal relations with application to group decision making

This paper is composed of two complementary parts. The first part is a formal investigation into the interplay of properties of reciprocal relations, how monotonicity relates to some natural and intuitive properties, including stochastic transitivity. The goal is to aggregate monotone reciprocal relations on a given set of alternatives. Monotonicity is expressed w.r.t. a linear order on the set of alternatives. The second part is a practical protocol to both determine the best fitting linear order underlying the alternatives, and construct a reciprocal relation monotone w.r.t. it. We formulate the problem as an optimization problem, where the aggregated linear order is that for which the implied stochastic monotonicity conditions are closest to being satisfied by the distribution of the input monotone reciprocal relations. We show that if stochastic monotonicity conditions are satisfied, a monotone reciprocal relation is easily found on the basis of the (possibly constructed) stochastically monotone reciprocal distributional relation.     

General results on the decomposition of transitive fuzzy relations

We study the transitivity of fuzzy preference relations, often considered as a fundamental property providing coherence to a decision process. We consider the transitivity of fuzzy relations w.r.t. conjunctors, a general class of binary operations on the unit interval encompassing the class of triangular norms usually considered for this purpose. Having fixed the transitivity of a large preference relation w.r.t. such a conjunctor, we investigate the transitivity of the strict preference and indifference relations of any fuzzy preference structure generated from this large preference relation by means of an (indifference) generator. This study leads to the discovery of two families of conjunctors providing a full characterization of this transitivity. Although the expressions of these conjunctors appear to be quite cumbersome, they reduce to more readily used analytical expressions when we focus our attention on the particular case when the transitivity of the large preference relation is expressed w.r.t. one of the three basic triangular norms (the minimum, the product and the Łukasiewicz triangular norm) while at the same time the generator used for decomposing this large preference relation is also one of these triangular norms. During our discourse, we pay ample attention to the Frank family of triangular norms/copulas.