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where Recognize QR In None Using Barcode Control SDK for Software Control to generate, create, read, scan barcode image in Software applications. Creating QRCode In None Using Barcode printer for Software Control to generate, create QR Code ISO/IEC18004 image in Software applications. Airport Planning
Denso QR Bar Code Decoder In None Using Barcode recognizer for Software Control to read, scan read, scan image in Software applications. QR Code Encoder In C#.NET Using Barcode printer for .NET Control to generate, create QR Code image in VS .NET applications. eliminated An illustration of the application of simple linear regression analysis is presented in Example Problem 53 Print QR In .NET Using Barcode generation for ASP.NET Control to generate, create QR Code ISO/IEC18004 image in ASP.NET applications. QR Code Encoder In .NET Framework Using Barcode encoder for VS .NET Control to generate, create QR Code JIS X 0510 image in VS .NET applications. Example Problem 53 The historical data shown in Table 51 could also be used to prepare a forecast of the annual passenger enplanements at the study airport in the design years 2010 and 2015 using a simple regression analysis In applying simple regression analysis to these data, let us assume that a relationship between the study airport annual enplanements (ENP) and the study area population (POP) is to be examined Therefore, it is assumed that a linear relationship of the form shown in Eq (51) exists between the variables ENP = a0 + a1(POP) Using a standard regression analysis computer program the relationship is found to be ENP = 3,047,032 + 138633(POP) where the coefficient of determination R2 is 0983815, the coefficient of correlation is 0991874, and the standard error of the estimate, yest is 55,5209 The regression line and the data points upon which this regression line is based are shown in Fig 55 The coefficient of determination indicates that there is an extremely good relationship between the annual enplanements at the study airport and the study area population, that is, 984 percent of the variation in the study airport annual enplanements is explained by the variation in the study area population The standard error of the estimate, however, indicates that there is a large range of error associated with forecasting with this equation, that is, there is a 68 percent probability that the forecast of annual enplanements at the study airport will have an error range of 55,5209 annual enplanements This may QR Code Printer In Visual Basic .NET Using Barcode maker for VS .NET Control to generate, create QRCode image in .NET applications. Painting Data Matrix 2d Barcode In None Using Barcode creator for Software Control to generate, create Data Matrix image in Software applications. Annual Airport Enplanement (Thousands) Create EAN13 In None Using Barcode drawer for Software Control to generate, create EAN13 Supplement 5 image in Software applications. Create Code39 In None Using Barcode maker for Software Control to generate, create USS Code 39 image in Software applications. ENP = 3047032 + 138633 POP
Print UPC Code In None Using Barcode printer for Software Control to generate, create UPCA image in Software applications. Generate USS Code 128 In None Using Barcode printer for Software Control to generate, create ANSI/AIM Code 128 image in Software applications. 300 Study Area Population (Thousands) Creating 2 Of 5 Interleaved In None Using Barcode generator for Software Control to generate, create ANSI/AIM I2/5 image in Software applications. Create Bar Code In Java Using Barcode creation for BIRT reports Control to generate, create bar code image in BIRT applications. FIGURE 55 Trend line forecast of study area population for Example Problem 53 Barcode Generator In Visual C#.NET Using Barcode drawer for .NET Control to generate, create barcode image in .NET framework applications. EAN13 Scanner In .NET Using Barcode reader for .NET Control to read, scan read, scan image in Visual Studio .NET applications. Forecasting for Airport Planning
ECC200 Encoder In Java Using Barcode generation for Android Control to generate, create Data Matrix ECC200 image in Android applications. Create UCC  12 In Java Using Barcode encoder for Java Control to generate, create EAN / UCC  13 image in Java applications. or may not be too high depending on the level of annual operations forecast in the future and the sensitivity of various components of the airport system to such variations Using a trend projection, it is forecast that the area population in the year 2010, as shown on Fig 56, is expected to be 363,000 The forecast of the annual enplanements at the airport in the year 2010 can be found by substitution into the regression equation yielding 1,985,300 annual enplanements Similarly, if the forecast of the area population in the year 2015 is expected to be 410,000, then the forecast of the annual enplanements at the airport in the year 2015 is found to be 2,636,900 Given the range in the standard error of the estimate, it could be expected that in the year 2010 there is a probability of 68 percent that the forecast could range between 1,985,300 55,500, or from 1,929,800 to 2,040,800 annual enplanements about 68 percent of the time Similarly, it could be expected that in the year 2015 the forecast could range between 2,636,900 55,500, or from 2,581,900 to 2,692,400 It is likely that this range in the forecasts is acceptable since it represents about a 2 to 3 percent error Barcode Encoder In Visual Studio .NET Using Barcode creation for ASP.NET Control to generate, create bar code image in ASP.NET applications. Creating Barcode In None Using Barcode creation for Office Word Control to generate, create barcode image in Office Word applications. It is interesting to compare the results found by the three different techniques used in Example Problems 51 through 53 The results compare very well and it gives one some degree of confidence in the results when the three forecasts compare well This is called redundancy in forecasting Based upon the results found in these example problems, a preferred forecast would be developed If there is no reason to suspect 600 Historical Data Study Area Population (Thousands) Forecast
410 400 363 200 2000 2005 Year 2010 2015
FIGURE 56 Trend line forecast of study area population for Example Problem 53 Airport Planning
that one technique is better than another, then a simple average might be used to develop the preferred forecast If this is done in these examples, then the preferred forecast for the year 2010 is about 2,000,000 annual enplaned passengers and in the year 2015 is 2,600,000 annual enplaned passengers The Federal Aviation Administration utilizes econometric models to determine national forecasts of US aviation demand The FAA Aerospace Forecast [8] provides a 12year outlook and view of the immediate future for aviation It is updated in March each year and includes aggregate level forecasts of the following: Passenger enplanements, revenue passenger miles, fleet, and hours flown for large carriers and regional commuters Cargo revenue ton miles and cargo fleet for large air carriers Fleet, hours, and pilots for general aviation Activity forecasts for FAA and contract towers by major user category The FAA Long Range Aerospace Forecasts [9] is a long range forecast that extends the 12year forecast to a longer time horizon, typically for a period of 25 years This forecast contains projections of aircraft, fleet and hours, air carrier and regional/commuter passenger enplanements, air cargo freight revenue tonmiles, pilots, and FAA workload measures The success in applying mathematical modeling techniques to ascertain the level of future activity depends to a large extent on the certainty associated with the independent variables and the relative influence of these variables on the dependent variable Simple and multiple regression analysis methods are often applied to a great variety of forecasting problems to determine the relationships between transport related variables and such explanatory factors as economic and population growth, market factors, travel impedance, and competitive forces Table 52 lists many of the variables required for various purposes in aviation planning studies

