Wavelet decomposition and its applications in aviation industry
Please cite this item using this persistent URL
http://hdl.handle.net/11693/15038Collections
Advisor
Ökten, Çağla
Publisher
Bilkent University
Abstract
This thesis analyzes the characteristic air traffic time series data of European
aviation industry by using wavelet decomposition. Firstly, time frequency representation
and discrete time wavelet decomposition is introduced by giving some theoretical
background and basic definitions. Then, the attributes of AEA data, i.e. load factor,
available seat kilometer and revenue passenger kilometer is analyzed both
geographically and based on prominent Airline operators. Furthermore, their relative
comparisons have led to unravel some underlying implications and their distinctive
interpretations for the airline industry