Utilization of artificial neural network in the evaluation of level of service in Canadian airports.

摘要

The air travel has been experiencing an increase in demand volume worldwide. As the number of passengers increases, the impact on the air transportation system increases. This will affect the level of service perceived by the passengers. Therefore, there is a necessity to develop a model to predict the perceived level of service to help the airport authorities to determine whether there is a need for improvement or not. A previous study was completed in Carleton University to develop a statistical model (based on Linear Regression Analysis) to predict the perceived level of service for baggage handling system in Canadian airports. Several models were developed to predict the perceived level of service for individual airports and for groups of airports classified according to their passenger volumes.; The present study is based on the utilization of the artificial neural network technique and its application to the data collected in the previous study. In addition, the ANN technique is applied on new data collected from Ottawa airport to measure the influence of the events of September 11 th on the passenger's perceived level of service. The results of the research showed that significant improvements could be achieved by the proper use of the ANN approach. Also, the results of Ottawa Airport showed that while there was no change in the perceived Level of Service for both cases; before and after September 11th the results showed remarkable change in the attitudes of passenger in the weights assigned to the parameters governing the overall perceived Level of Service of the Baggage Handling System.