首页|基于灰色-神经网络的民机需求组合预测

基于灰色-神经网络的民机需求组合预测

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民机数量是反映民航运输能力的重要标志,而对民机数量进行预测,能够研究分析未来民航业的发展趋势.本文重点研究了民机需求预测的模型架构和实施方法,首先以2013年到2020年民机数量和其他关键因素作为原始样本,然后把2021年的数据作为检验样本,最后通过构建灰色-神经网络组合预测模型对未来的民机需求进行预测.从预测结果来看,灰色模型GM(1,1)与反向传播(back propagation,BP)神经网络模型结合效果较好,组合模型预测精度高,充分证明了该模型的有效性和可行性,同时预测结果对分析未来航空运输情况也具有一定的参考意义.
Combination prediction of civil aircraft demand based on grey-neural network
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.

civil aircraftneural networkcombination prediction

庆豪、方志耕、王育红、邱玺睿

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南京航空航天大学经济与管理学院,江苏南京 211106

中国商用飞机有限责任公司上海飞机设计研究院,上海 201210

民机 神经网络 组合预测

国家自然科学基金国家自然科学基金

7227112452232014

2024

系统工程与电子技术
中国航天科工防御技术研究院 中国宇航学会 中国系统工程学会

系统工程与电子技术

CSTPCD北大核心
影响因子:0.847
ISSN:1001-506X
年,卷(期):2024.46(5)
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