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|Title:||Demand forecasting on air passenger travel to Sri Lanka : an evaluation of statistical, time series and artificial intelligence model||Authors:||Sivakumar, Tarshan||Keywords:||DRNTU::Engineering||Issue Date:||2018||Abstract:||With the immense popularity and convenience poised by air travel, passengers all over the world have been presented with the opportunity to travel to any parts of the world at any time. lATA recently published a press release forecasting that 7.2 billion people will travel by air by 2035 compared to 3.5 million at present. This calls for the need for tourist destinations like Sri Lanka to be ready in terms of air passenger volume and anticipating the level of infrastructural development required to cater to the increasing demand. The aim of this thesis is to estimate and forecast the air passenger demand that Sri Lanka may entail in the next 15 years. The focus is on finding a suitable forecasting model that presents optimal forecasting accuracy to predict the future. I 0 different forecasting models were experimented and evaluated in the thesis based on various evaluation criteria. The best perfom1ing forecasting model was then selected and the passenger demand was estimated for the next 15 years.||URI:||http://hdl.handle.net/10356/73287||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||MAE Theses|
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