Combination prediction of civil aircraft demand based on grey-neural network

被引：0
|
作者：
Qing H. [1 ]
Fang Z. [1 ]
Wang Y. [2 ]
Qiu X. [1 ]
机构：
[1] College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing
[2] Shanghai Aircraft Design and Research Institute, Commercial Aircraft Corporation of China, Shanghai
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2024年 / 46卷 / 05期
关键词：
civil aircraft; combination prediction; neural network;
D O I：
10.12305/j.issn.1001-506X.2024.05.19
中图分类号：
学科分类号：
摘要：
The number of civil aircraft is an important symbol that reflects the transport capacity of civil aviation. By predicting the number of civil aircraft, the development trend of civil aviation industry in the future can be studied and analyed. This paper focuses on the model architecture and implementation methods of civil aircraft demand forecasting. Firstly, the number of civil aircraft and other key factors from 2013 to 2020 are taken as the original samples, then the data of 2021 is taken as the test samples. Finally, the future demand of civil aircraft is predicted by constructing the combined prediction model of gray-neural network. From the prediction results, the combination of grey model GM (1,1) and back propagation (BP) neural network model has good effect, and the combination model has high prediction accuracy, which fully proves the validity and feasibility of this model. Meanwhile, the prediction results will also have some reference significance for analyzing the future air transportation situation. © 2024 Chinese Institute of Electronics. All rights reserved.
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页码：1665 / 1672
页数：7
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