@inproceedings{517cf8de9b804fddb072d22b6915cdcb,
title = "A terminal departure passenger traffic prediction method based on the RBF neural network",
abstract = "In order to solve the problem of terminal resources waste and improve the resource utilization efficiency of airport terminals, this paper proposes a prediction method based on the RBF neural network to predict future terminal departure passenger traffic at the next period. Data from Harbin Taiping International Airport are used to confirm the accuracy and applicability of this method in the field of terminal departure passenger traffic prediction.",
keywords = "RBF neural network, prediction, terminal departure passenger traffic",
author = "Shaowu Cheng and Ji Xu and Qiu Mu and Yaping Zhang",
year = "2014",
doi = "10.1061/9780784413623.004",
language = "英语",
isbn = "9780784413623",
series = "CICTP 2014: Safe, Smart, and Sustainable Multimodal Transportation Systems - Proceedings of the 14th COTA International Conference of Transportation Professionals",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "31--38",
booktitle = "CICTP 2014",
address = "美国",
note = "14th COTA International Conference of Transportation Professionals: Safe, Smart, and Sustainable Multimodal Transportation Systems, CICTP 2014 ; Conference date: 04-07-2014 Through 07-07-2014",
}