Terminal area take-off and landing capacity prediction method based on weather risk index

Abstract

The invention relates to a terminal area take-off and landing capacity prediction method based on a weather risk index. The terminal area take-off and landing capacity prediction method based on the weather risk index comprises the steps of abstracting control operation experience influencing a terminal area take-off and landing capacity; re-dividing the airspace structure of the terminal area according to control operation experience abstraction; acquiring a terminal area take-off and landing peak period and an initial sample; calculating features of the initial sample and establishing a model training set; establishing a random forest regression model according to the training set; and verifying and predicting the random forest regression model; re-dividing and modeling airspace structures related to the terminal area, extracting related features, associating the influence of convection weather with time period capacity, performing regression analysis by using flight historical data,training to obtain a terminal area take-off and landing capacity prediction model, and further inputting a weather prediction product to output capacity prediction under corresponding weather.

Description

technical field [0001] The invention relates to the field of forecasting capacity of an airport terminal area, in particular to a method for forecasting takeoff and landing capacity of a terminal area based on a weather risk index. Background technique [0002] The International Civil Aviation Organization proposed the aviation system block upgrade (ASBU) in the global air navigation plan (ICAO DOC9750), and my country also proposed the development and implementation strategy of the aviation system block upgrade of China's civil aviation accordingly. Airspace capacity is one of the 11 key performance areas published in the Global Air Navigation System Effectiveness Manual (ICAO DOC9883), which reflects the capabilities of the air traffic supply side. In addition, airspace capacity is a block in ASBU performance improvement domain 3, and effectively improving airspace capacity is the basis for realizing capacity flow balance and collaborative decision-making. [0003] DOC988...

AI Technical Summary

Problems solved by technology

At present, the capacity assessment technology under normal conditions (that is, without any external influence) in China has become mature, but the capacity prediction technology under abnormal conditions (such as: severe weather) is still in the preliminary stage. A single index multiplied by the nominal The capacity reduction method is too rough and cannot reflect the actual change of airspace capacity during operation. It is quite different from the actual situation and has low applicability. It cannot meet the refined management requirements of the civil aviation operation management department. The evaluation method based on computer simulation technology, It is suitable for capacity assessment work under specific scenarios. Since the basic radar reflectivity map reflecting the weather is updated every six minutes, this method cannot be consistent with the update frequency of meteorological elements, so it cannot comprehensively consider the actual operational factors that affect the The impact of airspace capacity changes, including weather changes, etc., based on controller workload evaluation methods generally rely on control simulators to reproduce control scenarios, and then extract factors that affect controller workload (such as: call frequency, etc.) and conduct quantitative analysis to obtain Airspace capacity, but it is difficult to reproduce and operate the control scenarios under the influence of weather, and can only be applied to the evaluation of specific scenarios (such as: only some thermal weather scenarios)

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