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Long-term and Short-term Forecasting Techniques for Regional Airport Planning
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Lång- och Kortsiktiga Prognostekniker för Hanterande av Regionala Flygplatser (Swedish)
Abstract [en]

The aim of this thesis is to forecast passenger demand in long term and short term perspectives at the Airport of Bologna, a regional airport in Italy with a high mix of low cost traffic and conventional airline traffic. In the long term perspective, time series are applied to forecast a significant growth of passenger volumes in the airport in the period 2016-2026. In the short term perspective, time-of-week passenger demand is estimated using two non-parametric techniques; local regression (LOESS) and a simple method of averaging observations. Using cross validation to estimate the accuracy of the estimates, the simple averaging method and the more complex LOESS method are concluded to perform equally well. Peak hour passenger volumes at the airport are observed in historical data and by use of bootstrapping, these are proved to contain little variability and can be concluded to be stable.

Abstract [sv]

Målet med denna uppsats är att prognosticera passagerefterfrågan i lång- och kortsiktigt perspektiv på Bologna Flygplats, en regional flygplats i Italien med hög mix av lågkostnadsbolag och konventionella flygbolag. I det långsiktiga perspektivet appliceras en tidsseriemodell som prognosticerar hög tillväxt i passagerarvolymer på flygplatsen under perioden 2016-2026. I det korta perspektivet uppskattas efterfrågan utefter tid i veckan med hjälp av två icke-parametriska modeller; local regression (LOESS) och en simpel metod som beräknar medelvärdet utav observationer. Med cross validation uppskattas precisionen i modellerna och det kan fastställas att den simpla medelvärdesmetoden och den mer avancerade LOESS-metoden har likvärdig precision. Passagerarvolymer på flygplatsen under högtrafik observeras i historisk data och med hjälp av bootstrapping visas att dessa volymer har låg variabilitet och det kan fastställas att de är stabila.

Place, publisher, year, edition, pages
TRITA-MAT-E, 2016:45
National Category
Probability Theory and Statistics
URN: urn:nbn:se:kth:diva-190839OAI: diva2:954470
External cooperation
University of Bologna
Subject / course
Mathematical Statistics
Educational program
Master of Science - Applied and Computational Mathematics
Available from: 2016-08-22 Created: 2016-08-17 Last updated: 2016-09-03Bibliographically approved

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