Research Article

A study on Air Passenger demand Forecasting from Egypt to Suadi Arabia

by  M.M. Mohie El-Din, N. I. Ghali, A. Sadek, A. A. Abouzeid
journal cover
Communications on Applied Electronics
Foundation of Computer Science (FCS), NY, USA
Volume 3 - Issue 1
Published: October 2015
Authors: M.M. Mohie El-Din, N. I. Ghali, A. Sadek, A. A. Abouzeid
10.5120/cae2015651868
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M.M. Mohie El-Din, N. I. Ghali, A. Sadek, A. A. Abouzeid . A study on Air Passenger demand Forecasting from Egypt to Suadi Arabia. Communications on Applied Electronics. 3, 1 (October 2015), 1-5. DOI=10.5120/cae2015651868

                        @article{ 10.5120/cae2015651868,
                        author  = { M.M. Mohie El-Din,N. I. Ghali,A. Sadek,A. A. Abouzeid },
                        title   = { A study on Air Passenger demand Forecasting from Egypt to Suadi Arabia },
                        journal = { Communications on Applied Electronics },
                        year    = { 2015 },
                        volume  = { 3 },
                        number  = { 1 },
                        pages   = { 1-5 },
                        doi     = { 10.5120/cae2015651868 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2015
                        %A M.M. Mohie El-Din
                        %A N. I. Ghali
                        %A A. Sadek
                        %A A. A. Abouzeid
                        %T A study on Air Passenger demand Forecasting from Egypt to Suadi Arabia%T 
                        %J Communications on Applied Electronics
                        %V 3
                        %N 1
                        %P 1-5
                        %R 10.5120/cae2015651868
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

This study employed the back-propagation neural network to forecast the air passenger demand from Egypt to Saudi Arabia. The factors that influence air passenger are identified, evaluated and analyzed by applying the back-propagation neural network on the annual data 2000 to 2010 by using visual gene developer package.

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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Airline Passenger Demand Forecasting Artificial Neural Network

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