NEURAL NETWORK BASED MODEL FOR PREDICTING THE NUMBER OF SLEEPING CARS IN RAIL TRANSPORT
Journal Title: INTERNATIONAL JOURNAL FOR TRAFFIC AND TRANSPORT ENGINEERING - Year 2015, Vol 5, Issue 1
Abstract
A Decision Support System based on Artificial Neural Network is developed to forecast the number of sleeping cars in rail transport. The inputs to the system consist of train route, month, type of sleeping car, number of berths (supply), number of departures, ticket price and GDP, while the output of the neural network is the number of sold tickets (demand). By comparing the results obtained through the model with those resulting from historical data, it has been found that the developed model is highly compatible with reality. The developed Decision Support System could be used for capacity planning purposes, because it is important for a rail operator to know in advance how many sleeping cars have to be available. All considered data are obtained from Serbian Railways.
Authors and Affiliations
Dragana Macura, Milica Šelmić, Branka Dimitrijević, Milorad Miletić
Keywords
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- EP ID EP132296
- DOI 10.7708/ijtte.2015.5(1).04
- Views 106
- Downloads 0
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