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A Geometric Fuzzy-Based Approach for Airport Clustering

机译:基于几何模糊的机场聚类方法

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Airport classification is a common need in the air transport field due to several purposes—such as resource allocation, identification of crucial nodes, and real-time identification of substitute nodes—which also depend on the involved actors’ expectations. In this paper a fuzzy-based procedure has been proposed to cluster airports by using a fuzzy geometric point of view according to the concept of unit-hypercube. By representing each airport as a point in the given reference metric space, the geometric distance among airports—which corresponds to a measure of similarity—has in fact an intrinsic fuzzy nature due to the airport specific characteristics. The proposed procedure has been applied to a test case concerning the Italian airport network and the obtained results are in line with expectations.
机译:由于多种目的,例如资源分配,关键节点的识别和替代节点的实时识别,机场分类是航空运输领域的普遍需求,这也取决于参与者的期望。本文提出了一种基于模糊的过程,根据单位超立方体的概念,利用模糊的几何观点对机场进行聚类。通过将每个机场表示为给定参考度量空间中的一个点,由于机场的特定特性,机场之间的几何距离(对应于相似度的度量)实际上具有内在的模糊性。拟议的程序已应用于有关意大利机场网络的测试案例,所获得的结果符合预期。

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