Civil aviation control sector classification method based on operation characteristics

Abstract

The invention discloses a civil aviation control sector classification method based on operation characteristics, and the method comprises the steps: collecting historical data, and carrying out the preprocessing; extracting required ADS-B track data in a specific sector range from historical data in combination with SQL and Python software, and obtaining sector classification indexes; providing an improved kernel fuzzy Cmean clustering algorithm based on a genetic algorithm to obtain a better clustering effect; setting a clustering effectiveness index, and determining the number of sector classification categories; taking the extracted key classification factor as algorithm input, and outputting a sector clustering result; and determining classification characteristics of the selected samples according to a clustering result, and analyzing and verifying multi-dimensional attributes of traffic operation of different types of sectors in combination with numerical distribution of the samples. According to the method, the sectors are classified from macroscopic overall operation characteristics, the operation characteristics of different types of sectors can be known, an optimizationbasis is provided for control operation management, and meanwhile theoretical support can be provided for innovative development of sector classification special management, dynamic configuration, remote control and the like.

Description

technical field [0001] The invention belongs to the field of air traffic management and planning, and in particular relates to a method for classifying civil aviation control sectors based on operating characteristics. Background technique [0002] The continuous increase of flight volume and the subsequent insufficient supply of civil aviation domain resources have caused flight regularity problems to become increasingly prominent. Redesign sectors to make them smaller, thereby reducing the workload of controllers in each sector The approach is not very cost-effective, it requires more controllers to manage sector operations, more equipment to display sector information, increased coordination between aircraft and ATC and between controllers. To classify sectors, analyze the similarities and differences between sectors from multiple dimensions such as structure, flow, and complexity of different sectors, deeply grasp the operating characteristics of sectors, and find out th...

AI Technical Summary

Problems solved by technology

[0003] At present, most studies on sector classification mainly start from the sector’s operating mode, traffic flow structure, and complexity indicators; the sector samples selected for the research are relatively small, so in order to increase the number of samples, generally from the time period Considering the complex situation, there are relatively few studies and analyzes on the overall operation characteristics of the sector

At the same time, in previous studies, hard clustering algorithms were often used to divide sectors into categories or busy periods and levels, and the division results were unreasonable to a certain extent.

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