FORECASTING AIR TRAFFIC VOLUMES USING SMOOTHING TECHNIQUES
For many years, researchers have been using statistical tools to estimate parameters of macroeconomic models. Forecasting plays a major role in logistic planning and it is an essential analytical tool in countries’ air traffic strategies. In recent years, researchers are developing new techniques fo...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Turkish Air Force Academy
2014-01-01
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| Series: | Havacılık ve Uzay Teknolojileri Dergisi |
| Subjects: | |
| Online Access: | http://www.jast.hho.edu.tr/JAST/index.php/JAST/article/view/156/144 |
| _version_ | 1797921567332630528 |
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| author | Emrah Önder Sultan Kuzu |
| author_facet | Emrah Önder Sultan Kuzu |
| author_sort | Emrah Önder |
| collection | DOAJ |
| description | For many years, researchers have been using statistical tools to estimate parameters of macroeconomic models. Forecasting plays a major role in logistic planning and it is an essential analytical tool in countries’ air traffic strategies. In recent years, researchers are developing new techniques for estimation. In particular, this research focuses on the application of smoothing techniques and estimation of air traffic volume. In this study four air traffic indicators including total passenger traffic, total cargo traffic, total flight traffic and commercial flight traffic were used for forecasting. Also seasonal effects of these parameters were investigated. As analysis tools, classical time series forecasting methods such as moving averages, exponential smoothing, Brown's single parameter linear exponential smoothing, Brown’s second-order exponential smoothing, Holt's two parameter linear exponential smoothing and decomposition methods applied to air traffic volume data between January 2007 and May 2013. The study focuses mainly on the applicability of Traditional Time Series Analysis (Smoothing & Decomposition Techniques). To facilitate the presentation, an empirical example is developed to forecast Turkey’s four important air traffic parameters. Time Series statistical theory and methods are used to select an adequate technique, based on residual analysis. |
| first_indexed | 2024-04-10T14:17:35Z |
| format | Article |
| id | doaj.art-8474ee6ff81444809c10ed27618aac99 |
| institution | Directory Open Access Journal |
| issn | 1304-0448 1304-0448 |
| language | English |
| last_indexed | 2024-04-10T14:17:35Z |
| publishDate | 2014-01-01 |
| publisher | Turkish Air Force Academy |
| record_format | Article |
| series | Havacılık ve Uzay Teknolojileri Dergisi |
| spelling | doaj.art-8474ee6ff81444809c10ed27618aac992023-02-15T16:09:28ZengTurkish Air Force AcademyHavacılık ve Uzay Teknolojileri Dergisi1304-04481304-04482014-01-01716585FORECASTING AIR TRAFFIC VOLUMES USING SMOOTHING TECHNIQUESEmrah Önder0Sultan Kuzu1Istanbul UniversityIstanbul UniversityFor many years, researchers have been using statistical tools to estimate parameters of macroeconomic models. Forecasting plays a major role in logistic planning and it is an essential analytical tool in countries’ air traffic strategies. In recent years, researchers are developing new techniques for estimation. In particular, this research focuses on the application of smoothing techniques and estimation of air traffic volume. In this study four air traffic indicators including total passenger traffic, total cargo traffic, total flight traffic and commercial flight traffic were used for forecasting. Also seasonal effects of these parameters were investigated. As analysis tools, classical time series forecasting methods such as moving averages, exponential smoothing, Brown's single parameter linear exponential smoothing, Brown’s second-order exponential smoothing, Holt's two parameter linear exponential smoothing and decomposition methods applied to air traffic volume data between January 2007 and May 2013. The study focuses mainly on the applicability of Traditional Time Series Analysis (Smoothing & Decomposition Techniques). To facilitate the presentation, an empirical example is developed to forecast Turkey’s four important air traffic parameters. Time Series statistical theory and methods are used to select an adequate technique, based on residual analysis.http://www.jast.hho.edu.tr/JAST/index.php/JAST/article/view/156/144Air Traffic VolumeForecastingSmoothingDecompositionTime SeriesTurkey |
| spellingShingle | Emrah Önder Sultan Kuzu FORECASTING AIR TRAFFIC VOLUMES USING SMOOTHING TECHNIQUES Havacılık ve Uzay Teknolojileri Dergisi Air Traffic Volume Forecasting Smoothing Decomposition Time Series Turkey |
| title | FORECASTING AIR TRAFFIC VOLUMES USING SMOOTHING TECHNIQUES |
| title_full | FORECASTING AIR TRAFFIC VOLUMES USING SMOOTHING TECHNIQUES |
| title_fullStr | FORECASTING AIR TRAFFIC VOLUMES USING SMOOTHING TECHNIQUES |
| title_full_unstemmed | FORECASTING AIR TRAFFIC VOLUMES USING SMOOTHING TECHNIQUES |
| title_short | FORECASTING AIR TRAFFIC VOLUMES USING SMOOTHING TECHNIQUES |
| title_sort | forecasting air traffic volumes using smoothing techniques |
| topic | Air Traffic Volume Forecasting Smoothing Decomposition Time Series Turkey |
| url | http://www.jast.hho.edu.tr/JAST/index.php/JAST/article/view/156/144 |
| work_keys_str_mv | AT emrahonder forecastingairtrafficvolumesusingsmoothingtechniques AT sultankuzu forecastingairtrafficvolumesusingsmoothingtechniques |