Civil Aviation Passenger Traffic Forecasting: Application and Comparative Study of the Seasonal Autoregressive Integrated Moving Average Model and Backpropagation Neural Network
Weifan Gu,
Baohua Guo,
Zhezhe Zhang
et al.
Abstract:With the rapid development of China’s aviation industry, the accurate prediction of civil aviation passenger volume is crucial to the sustainable development of the industry. However, the current prediction of civil aviation passenger traffic has not yet reached the ideal accuracy, so it is particularly important to improve the accuracy of prediction. This paper explores and compares the effectiveness of the backpropagation (BP) neural network model and the SARIMA model in predicting civil aviation passenger t… Show more
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