Article
NEURAL NETWORK BASED MODEL FOR PREDICTING THE NUMBER OF SLEEPING CARS IN RAIL TRANSPORT
DOI: 10.7708/ijtte.2015.5(1).04
5 / 1 / 29-35 Pages
Author(s)
Dragana Macura - University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, 11000 Belgrade, Serbia -
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.
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Acknowledgements:
This work was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia through the projects TR36002 and TR36022 for the period 2011-2014.
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