基于灰色-神经网络的民机需求组合预测

doi:10.12305/j.issn.1001-506X.2024.05.19

Abstract

Abstract:

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.

Key words: civil aircraft, neural network, combination prediction

CLC Number:

N945

Hao QING, Zhigeng FANG, Yuhong WANG, Xirui QIU. Combination prediction of civil aircraft demand based on grey-neural network[J]. Systems Engineering and Electronics, 2024, 46(5): 1665-1672.

Figures/Tables 17

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年份	X₁	X₂	X₃	X₄	X₅	Y
2013	9.53	671.72	35 397.00	592 963.00	2 876.00	2 145.00
2014	9.51	748.12	39 195.00	635 910.00	3 142.00	2 370.00
2015	9.49	851.65	43 618.00	688 858.20	3 326.00	2 650.00
2016	9.41	962.51	48 796.00	746 395.10	3 794.00	2 950.00
2017	9.49	1 083.08	55 156.00	832 035.90	4 418.00	3 296.00
2018	9.36	1 206.53	61 173.77	919 281.10	4 945.00	3 639.00
2019	9.33	1 293.25	65 993.42	986 515.20	5 521.00	3 818.00
2020	6.49	798.51	41 777.82	1 015 986.20	5 581.00	3 903.00
2021	6.62	856.75	44 055.74	1 143 670.00	4 864.00	3 946.00

年份	原始值	拟合值	误差	相对误差/%
2013	2 145	2 145	0	0.0
2014	2 370	2 492	-122	-5.1
2015	2 650	2 706	-56	-2.1
2016	2 950	2 938	12	0.4
2017	3 296	3 190	106	3.2
2018	3 639	3 464	175	4.8
2019	3 818	3 761	57	1.5
2020	3 903	4 083	-180	-4.6
2021	3 946	4 433	-487	-12.4

年份	X₁	X₂	X₃	X₄	X₅	Y
2013	0.120 3	0.079 3	0.081 3	0.078 4	0.074 8	0.074 7
2014	0.120 0	0.088 3	0.090 1	0.084 1	0.081 7	0.082 5
2015	0.119 8	0.100 5	0.100 2	0.091 1	0.086 5	0.092 3
2016	0.118 8	0.113 6	0.112 1	0.098 7	0.098 6	0.102 7
2017	0.119 8	0.127 8	0.126 7	0.110 0	0.114 9	0.114 8
2018	0.118 1	0.142 4	0.140 6	0.121 6	0.128 6	0.126 7
2019	0.117 8	0.152 6	0.151 7	0.130 5	0.143 5	0.133 0
2020	0.081 9	0.094 3	0.096 0	0.134 4	0.145 1	0.135 9
2021	0.083 6	0.101 1	0.101 2	0.151 2	0.126 4	0.137 4

年份	原始值	拟合值	误差	相对误差/%
2013	2 145	2 188	-43	-2.0
2014	2 370	2 322	48	2.0
2015	2 650	2 588	62	2.3
2016	2 950	2 966	-16	-0.5
2017	3 296	3 223	73	2.2
2018	3 639	3 682	-43	-1.2
2019	3 818	3 713	105	2.8
2020	3 903	3 948	-45	-1.2
2021	3 946	3 572	374	9.5

年份	X₁	X₂	X₃	X₄	X₅	X₆	Y
2013	0.120 3	0.079 3	0.081 3	0.078 4	0.074 8	0.073 4	0.074 7
2014	0.120 0	0.088 3	0.090 1	0.084 1	0.081 7	0.085 3	0.082 5
2015	0.119 8	0.100 5	0.100 2	0.091 1	0.086 5	0.092 6	0.092 3
2016	0.118 8	0.113 6	0.112 1	0.098 7	0.098 6	0.100 6	0.102 7
2017	0.119 8	0.127 8	0.126 7	0.110 0	0.114 9	0.109 2	0.114 8
2018	0.118 1	0.142 4	0.140 6	0.121 6	0.128 6	0.118 6	0.126 7
2019	0.117 8	0.152 6	0.151 7	0.130 5	0.143 5	0.128 7	0.133 0
2020	0.081 9	0.094 3	0.09 6	0.134 4	0.145 1	0.139 8	0.135 9
2021	0.083 6	0.101 1	0.101 2	0.151 2	0.126 4	0.151 8	0.137 4

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

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年份	原始值	拟合值	误差	相对误差/%
2013	2 145	2 145	-0.159 9	-0.007 5
2014	2 370	2 369	0.847 5	0.035 8
2015	2 650	2 691	-40.782 9	-1.539 0
2016	2 950	2 949	0.764 1	0.025 9
2017	3 296	3 323	-26.556 9	-0.805 7
2018	3 639	3 638	0.556 1	0.015 3
2019	3 818	3 819	-1.361 0	-0.035 6
2020	3 903	3 903	0.359 7	0.009 2
2021	3 946	3 883	63.461 6	1.608 3

年份	X₁	X₂	X₃	X₄	X₅	X₆
2022	6.89	978.32	48 238.36	1 236 520.1	3 966	4 814
2023	8.67	1 165.46	62 773.24	1 318 560.0	4 238	5 227
2024	9.48	1 308.27	68 996.35	1 465 421.2	4 624	5 675

年份	2022	2023	2024
飞机数量/架	4 012	4 238	4 547