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Definition of general aggregation operators through similarity relations

机译:通过相似关系定义一般聚合算子

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Various extensions of the original max and min aggregation operators in fuzzy set theory are successfully used in practical applications, but lack a clear conceptual model supporting them. Giving these operators a meaningful and simple interpretation is the topic of this paper. Aggregation operators are seen as different methods to measure distances to the essential reference points of the feature space, called Ideals. It has been proved that every general aggregation operator can be associated with a corresponding metric, in which the result of its application is the distance to the Ideal. Some widely used operators correspond to familiar l-p norms, and new operators can be defined by specifying different metrics. Heterogeneous combinations of ANDs and ORs are treated in such a way that the distributivity and De Morgan's laws hold. Applications to fuzzy constraint satisfaction problem and fuzzy control are discussed and interpreted geometrically. Classical operators are particualr cases of the proposed semantic model, and several other examples are given.
机译:模糊集理论中原始最大和最小聚集算符的各种扩展已在实际应用中成功使用,但缺少支持它们的清晰概念模型。为这些运算符提供有意义且简单的解释是本文的主题。聚合运算符被视为测量到要素空间基本参考点的距离(称为理想)的不同方法。已经证明,每个通用聚合算子都可以与一个对应的度量相关联,其中其应用的结果就是与理想值的距离。一些广泛使用的运算符对应于熟悉的l-p规范,并且可以通过指定不同的指标来定义新的运算符。 AND和OR的异类组合以分布和De Morgan定律成立的方式处理。对模糊约束满足问题和模糊控制的应用进行了讨论和几何解释。经典运算符是所提出语义模型的特例,并给出了其他一些示例。

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