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By Norman J. Ashford at al.
Аэропорт инжиниринг: планирование, проектирование и развитие аэропортов 21-го века. Издание 4-е.
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Additional info for Airport Engineering. Planning Design and Development of 21st Century Airports (4th edition)
MUS . S. , local to national and local to regional) Econometric modeling, where aviation activities are tied to other economic measures Simulation—a technique that is separate and independent from demand forecasting used to provide high-fidelity operational snapshot estimates of traffic flows across a network through the airport These techniques are described below. Trend Projection Trend projection of demand relies on the quality of the historical data (time series) and the stability of growth over time.
In the United States, this method constitutes an essential part of the regionallevel component of the Comprehensive Airport Demand Forecast Framework described elsewhere in this chapter. There are three variations for this technique: Method A 1. Determine the percentage of national enplaned passengers that the airport has attracted in the past. 2. Adjust this percentage to reflect anticipated abnormal growth trends. 3. Obtain data for national passenger traffic for the design year. 4. Calculate step-down design figures as the product of the percentage of step 2 and the national figure from step 3.
Xn = independent predictive variables a1 , . . , an = regression coefficients In developing the econometric models it is important to ensure that not only does a statistical correlation exist for the relationship, but also there is a logical or implied causal relationship between the predicted and predictive variables. Moreover, it is also an important statistical requirement that predictive variables are independent of each other. 4 Integrated Demand Forecast Framework 33 population to the airport.
Airport Engineering. Planning Design and Development of 21st Century Airports (4th edition) by Norman J. Ashford at al.