管制扇区运行稳度K-means聚类与分析

doi:10.16265/j.cnki.issn1003-3033.2024.07.0197

摘要/Abstract

摘要：

为更好地分析管制扇区运行存在的稳定亚安全状态和不稳定亚安全状态,使用K-means算法划分超容比(ECR)、滞留度和飞行姿态混合比3个管制扇区运行稳度评价指标聚类,确定管制扇区运行稳度最佳等级划分;聚类分析单一指标,获得各等级对应的指标阈值,结合熵权法计算的指标权重,遵循隶属度最大原则,获取各时间段的管制扇区运行稳度等级,构建管制扇区运行稳度综合评价模型;选取厦门01号扇区的实际飞行数据,从稳度和趋度2个角度更加全面地分析管制扇区运行态势。结果表明:管制扇区运行稳度等级划分为3类时效果最好;稳度受空中交通流和管制状况的影响会随时间而变化,尤其7:30—9:15和20:00—21:00这2 个时间段管制扇区运行稳度的变化最为明显,需引起管制员高度重视,提高空域运行安全。

关键词: 管制扇区, 运行稳度, 趋度, K-means聚类, 综合评价

Abstract:

In order to better analyze the stable sub-safety state and unstable sub-safety state existing in control sector operation, K-means algorithm was used to cluster three control sector operation stability evaluation indicators of excess-capacity ratio(ECR), retention degree and flight attitude mixing ratio so that the optimal classification of the operation stability of control sector was determined. The index threshold corresponding to each level was obtained by clustering analysis of a single index. Combined with the index weight calculated by the entropy weight method, the operational stability level of the control sector in each time period was obtained according to the principle of maximum membership degree. Then, the comprehensive evaluation model of control sector operation stability was constructed. The actual flight data of Xiamen No.01 sector was selected to more comprehensively analyze operation situation of control sector from the perspectives of stability and trend. The results show that the best effect is obtained when the control sector operation stability level is divided into three categories. The stability varies with time due to the influences of air traffic flow and control conditions, especially in the two time periods of 7: 30-9: 15 and 20: 00-21: 00, when the change of stability is most obvious. The controllers need to pay great attention to improving the safety of airspace operations.

Key words: control sector, operation stability, trend, K-means clustering, comprehensive evaluation

中图分类号:

X949

岳仁田, 杨果果. 管制扇区运行稳度K-means聚类与分析[J]. 中国安全科学学报, 2024, 34(7): 98-104.

YUE Rentian, YANG Guoguo. K-means clustering and analysis of operation stability for control sector[J]. China Safety Science Journal, 2024, 34(7): 98-104.

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序列号	ECR	R	M
1	0	0.857	0
2	0.286	0.195	0.200
3	0.095	0.571	0.163
4	0.381	0.619	0.446
5	0.714	0.626	0.760
6	0.857	0.371	0.795
︙	︙	︙	︙
28	0.714	0.371	0.727
29	0.857	0.482	0.864
30	0.571	0.122	0.551
︙	︙	︙	︙
61	0.286	0.195	0.262
62	0.571	0.429	0.614
63	0.476	0.200	0.431
64	0.238	0.673	0.226

指标/等级	3	2	1
ECR	[0,0.357]	(0.357,0.643]	(0.643,1]
R	[0,0.292]	(0.292,0.595]	(0.595,1]
M	[0,0.403]	(0.403,0.636]	(0.636,1]

时间序列	稳度	趋度	时间序列	稳度	趋度
1	0.75	0	31	0.5	0.125
2	0.75	0	32	0.625	0
3	0.75	-0.125	33	0.625	0.125
4	0.625	-0.125	34	0.75	0
5	0.5	-0.125	35	0.75	0
6	0.375	-0.125	36	0.75	0
7	0.25	0.25	37	0.75	-0.125
8	0.5	0.125	38	0.625	0
9	0.675	0.125	39	0.625	0
10	0.75	0	40	0.625	0
11	0.75	-0.25	41	0.625	0
12	0.5	0	42	0.625	0.125
13	0.5	0	43	0.75	-0.25
14	0.5	0	44	0.5	0
15	0.5	0.25	45	0.5	0.125
16	0.75	0.125	46	0.625	-0.125
17	0.875	0	47	0.5	0.25
18	0.875	0.125	48	0.75	-0.125
19	1	-0.125	49	0.625	0
20	0.875	0	50	0.625	0.125
21	0.875	0	51	0.75	0
22	0.875	-0.125	52	0.75	0.25
23	0.75	0.125	53	1	-0.25
24	0.875	0	54	0.75	-0.125
25	0.875	-0.125	55	0.625	-0.125
26	0.75	0.125	56	0.5	-0.25
27	0.875	-0.125	57	0.25	0.125
28	0.75	-0.125	58	0.375	0.125
29	0.625	0	59	0.5	0
30	0.625	-0.125	60	0.5	0