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The Demand Forecasting For The Checked Baggage Of The Departing Passengers In The Airport Terminal

Posted on:2014-08-27Degree:MasterType:Thesis
Country:ChinaCandidate:Z C YangFull Text:PDF
GTID:2252330422951558Subject:Transportation planning and management
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With the development of China’s aviation industry, the volume of China’s civilaviation passenger is growing rapidly. As the volume of passenger is increasing, itoften occurs that the departing passengers will wait for a long time at the check-inarea. It is likely to cause disorder in airport terminal. This will lead to affect thequality of service and the operation of the flights on schedule. Baggage handling isone of key factors that decide the time of departing passengers in the terminal. Onlyaccurately grasping the needs of the checked baggage of departing passenger,terminal allocates the device resources timely and accurately. That effectivelyreduces the time of passengers in the terminal, ensures that departing passengersboard the plane quickly and the flights safely fly.The paper makes a research on the checked baggage of the departingpassengers in the airport terminal, and chooses BP neural network to quantitativelypredict demand for the checked baggage of the departing passengers in the sameflight. Firstly by analyzing the particularity of air transport, it proposes quantitativeindicators and influencing factors for the demand of the checked baggage, andexplains the mechanism of their respective roles. Then, based on comparison ofvarious forecasting methods, it is considered that BP neural network is applicable tosolve this problem. This paper establishes the forecasting model theory for thedemand of the checked baggage through the research and analysis on BP neuralnetwork theory. At last, that establishes the optimal network structure of forecastingmodel through many trials and creates the forecasting model for the checkedbaggage of the departing passengers in the airpo rt termina l. At the same, this paperconducts a series of improvements and optimization about the model. Afterverification of the actual data, the forecasting model is scientific and feasible.Through the establishment of forecasting models for the checked baggage,airport staff can choose the rational number of counters for the departing passengers,assign personnel and allocate the device resources about the checked baggagescientifically. That reduces the waste of the device resources, ensures the norma loperation of all kinds of homework in the airport termina l and improves the servicelevel of civil aviation transportation.
Keywords/Search Tags:airport terminal, departing passengers, checked baggage, BP neuralnetwork, demand forecasting
PDF Full Text Request
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