Forecasting Passenger Numbers in Saudi Arabian Airlines Flights
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 4
Abstract
Forecasting Is A Prediction Of Future After Studying The Past;It Is A Planning Tool That Helps Management For Budgeting, Planning, And Estimating Future Expectations. Exploring The Pattern Of The Data Is The Way To Select Appropriate Forecasting Techniques To The Data. Time Series Data For Passenger In Saudi Arabian Airlines Were Collected In Hijri And Gregorian Calendars, The Data Were Monthly For Ten Years In Gregorian, However, Hijri Data Were Only For About Three Years, The Data Was Transformed From Gregorian To Hijri To Complete The Missing Gab.The Data For Both Calendars Are Of Trend Pattern And Moderate Seasonality. Eightsuitabletime Series Forecasting Models Available In Minitab And Excel Software Are Checked To Apply For Both Hijri And Gregorian Data. These Time Series Forecasting Models Are:Naïve For Trend And Seasonality, Double Exponential Smoothing, Seasonal Exponential Smoothing, Decomposition, Trend Models,ARIMA, Regression For Seasonal Data And Combining Forecasts. Since The Trend Equation With Smaller Measures Of Errors Is Curvilinear, Many Alternatives Of The Regression For Seasonal Data Method Are Proposedwith Nonlinear Expressions Of The Time Independent Variable. The Nonlinear Expressions Are Different Power Terms And Also S-Curve Equation Of The Time Independent Variable.Each Forecasting Method Is Checked For Adequacy And For The Measures Of Forecasting Errors And The Best Method Is Used To Perform The Long-Term Forecasting For The Upcoming 5 Years.
Authors and Affiliations
Said Ali Hassan, AbdulazizTariq Qadi
Keywords
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