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.
A Geometric Fuzzy-Based Approach for Airport Clustering / Postorino, Mn; Versaci, Mario. - In: ADVANCES IN FUZZY SYSTEMS. - ISSN 1687-7101. - 2014:(2014). [10.1155/2014/201243]
A Geometric Fuzzy-Based Approach for Airport Clustering
VERSACI, Mario
2014-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.