基于灰色聚类的管制扇区运行健康识别方法
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x949

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民航联合基金(U1533112)、自然基金面上项目(61571441)和科技部国家重点研发计划(2016YFB0502405)


Health Identification of Sector Control Operation Based on Gray Clustering Method
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    摘要:

    对不同健康程度的管制扇区运行状态识别有助于全面把握交通运行情况,对空管安全评估、扇区划分、流量管理具有一定的应用价值。深入分析管制扇区交通时空运行特性,基于实际运行数据建立了管制扇区运行健康识别方法。建立饱和度、瞬时饱和度、滞留度、未来15分钟流量、管制工作负荷程度5项管制扇区运行健康评估指标,利用主客观组合赋权法确定各评估指标权重,基于灰色聚类方法对管制扇区运行健康状态等级进行识别。以厦门1号扇区的交通数据进行了实例分析,结果表明:管制扇区运行健康态势是交通宏观动态特征和微观复杂特征相互作用的结果,本文提出的管制运行健康识别方法有效,计算过程简单可行。

    Abstract:

    The health status identification of ATM sector can help to comprehensively understand air traffic operation situation, and has certain application value in ATC safety assessment, sector division and air traffic flow management. Based on the temporal and spatial characteristics of traffic flow in ATM sector, a sector control operation health identification method is established with the air traffic operational data. We established five health evaluation indicators for sector control operation, such as saturation degree, instantaneous saturation degree, retention degree, traffic demand of next 15 minutes, and ATC workload level. Then, the subjective and objective combination weighting method was used to determine the weight of each evaluation indicator. And then, the health classification method of the sector control operation was built with gray clustering theory and verified with the operation data of Xiamen No.1 sector. The results show that the health status is the result of the interaction between macroscopic dynamic characteristics and complicated microscopic features; the proposed method is effective and the calculation process is simple and feasible.

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岳仁田,韩娜. 基于灰色聚类的管制扇区运行健康识别方法[J]. 科学技术与工程, 2020, 20(16): 6697-6702.
Yue Rentian, Han Na. Health Identification of Sector Control Operation Based on Gray Clustering Method[J]. Science Technology and Engineering,2020,20(16):6697-6702.

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  • 收稿日期:2019-09-17
  • 最后修改日期:2020-05-31
  • 录用日期:2019-11-24
  • 在线发布日期: 2020-06-29
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