Long-term and Short-term Forecasting Techniques for Regional Airport Planning
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.
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