Application of BP Neural Network in Airport Passenger Volume Forecast

It is particularly important to study and analyze the airport passenger volume and its influencing factors for the development of China's aviation industry and tourism industry. Based on BP neural network, the passenger volume prediction model of Xinzheng International Airport is established, and through the analysis and summary of the existing literature, many factors affecting the airport freight volume are analyzed, and four main influencing factors are selected as the input layer, and then the model is trained by matlab software. It can be concluded from the results that the maximum prediction error rate is less than 5%, which shows that the model used in this paper has high accuracy, and can provide a new way for airport freight volume prediction, so as to improve the forecasting accuracy of airport freight volume in China and provide reference for local airport construction and development planning.