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Airport forecasting issue 45 tls 2020 - Toulouse Airport

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Mohammed Awad
Mohammed Awad

Airport Traffic Forecasting for Toulouse Airport Two Scenarios used to explore the possible out comes based on R-squared values,

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Airport Forecasting - 2020 (Issue No. 45) Toulouse Airport (TLS) There is no means to forecast, if we do not hold it in the right time. Long time ago as we were in the schools we learnt that – 80% value of R – square was accepted level for best fitting for the Data. Today, in practice and real life, the margin of fitting is too tight, and the change in values of R- square has a significant meaning on final results. Therefore, we are exploring all the possible option of the outcomes – that put the top management on a solid ground to stand and get a clear picture for the future. Annual Passengers Forecast: There are three possible outputs for forecasting, positive growth, leveling (Zero Growth) and negative trend, and the best way to set up annual target and minimize the data discrepancy is to address the data by two trend models using the concept of 12 rolling months. First – General Trend Model using the concept of Straight Line equation – defining general trend. Second – Most Recent Data Trend Model Using a Polynomial Model – Second-degree equation. This reflects the impact of most recent data on the path of general trend. The mid-point is the most convenient forecast annual result at Dec 2020. So as long as the gap between two models is small, the more accurate approaching value for setting annual target otherwise we have to select the half way distance between two extreme targets of these two models provided that Dec 2020 > Dec 2019. Scenario 1: Preset Annual Target = Passengers = 9,673,392 Pax. At annual growth 1.2 % and R- square = 95.01 % and boundary error range -5.18 to +6.57 %, we select preset value for Dec 2019 = 9,673,392 as Dec 2019 > Dec 2020 for first scenario. – (Recommend) Scenario 2: Optimum Solution. = Passengers = 9,969,622 Pax. This is an optimum solution without any pre-set targets or constrains that governed the analysis, the outcome results = Pax 2020 = 9,969,622, at annual growth 2.42 %, R- square = 95.56 % and boundary error range -3.01 to +5.57 %. (below : how to read the Graph) By: Mohammed Salem Awad Aviation Consultant Data Source: https://ec.europa.eu/eurostat/data/database
22 SettingTargets1st Scenario2nd Scenario

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Airport forecasting issue 45 tls 2020 - Toulouse Airport

  • 1. Airport Forecasting - 2020 (Issue No. 45) Toulouse Airport (TLS) There is no means to forecast, if we do not hold it in the right time. Long time ago as we were in the schools we learnt that – 80% value of R – square was accepted level for best fitting for the Data. Today, in practice and real life, the margin of fitting is too tight, and the change in values of R- square has a significant meaning on final results. Therefore, we are exploring all the possible option of the outcomes – that put the top management on a solid ground to stand and get a clear picture for the future. Annual Passengers Forecast: There are three possible outputs for forecasting, positive growth, leveling (Zero Growth) and negative trend, and the best way to set up annual target and minimize the data discrepancy is to address the data by two trend models using the concept of 12 rolling months. First – General Trend Model using the concept of Straight Line equation – defining general trend. Second – Most Recent Data Trend Model Using a Polynomial Model – Second-degree equation. This reflects the impact of most recent data on the path of general trend. The mid-point is the most convenient forecast annual result at Dec 2020. So as long as the gap between two models is small, the more accurate approaching value for setting annual target otherwise we have to select the half way distance between two extreme targets of these two models provided that Dec 2020 > Dec 2019. Scenario 1: Preset Annual Target = Passengers = 9,673,392 Pax. At annual growth 1.2 % and R- square = 95.01 % and boundary error range -5.18 to +6.57 %, we select preset value for Dec 2019 = 9,673,392 as Dec 2019 > Dec 2020 for first scenario. – (Recommend) Scenario 2: Optimum Solution. = Passengers = 9,969,622 Pax. This is an optimum solution without any pre-set targets or constrains that governed the analysis, the outcome results = Pax 2020 = 9,969,622, at annual growth 2.42 %, R- square = 95.56 % and boundary error range -3.01 to +5.57 %. (below : how to read the Graph) By: Mohammed Salem Awad Aviation Consultant Data Source: https://ec.europa.eu/eurostat/data/database