A Basic Study of the Forecast of Air Transportation Networks Using Different Forecasting Methods

Abstract

This research applies network structuring theories to the aviation domain and predicts aviation network growth, considering a flight connection between airports as a link between nodes. Our link prediction approach is based on network structure information, and to improve prediction accuracy, it is necessary to estimate the mechanism of aviation network growth. This research critically evaluates the prediction accuracy of two methods: the receiver operating characteristic curve method (ROC) and the logistic regression method. We propose a four-step method to evaluate the relative predictive accuracy among different link prediction methods. A case study of US aviation networks indicated that the ROC method provided better prediction accuracy compared with the logistic regression method. This result suggests that tuning of the prediction distribution and the regression model coefficients can further improve the accuracy of the logistic regression method.