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.
Titolo: | A Geometric Fuzzy-Based Approach for Airport Clustering |
Autori: | |
Data di pubblicazione: | 2014 |
Rivista: | |
Handle: | http://hdl.handle.net/20.500.12318/7085 |
Appare nelle tipologie: | 1.1 Articolo in rivista |