Airspace network capacity prediction method in severe weather

A technology for severe weather and forecasting methods, applied in biological neural network models, climate sustainability, instruments, etc., can solve problems such as difficult to adapt to complex air traffic operation scenarios, spatial impact, and the interconnection of time dimensions to improve decision-making The effect of quality and sophistication, improving interpretability, and reducing regulatory pressure

CN114722551AActive Publication Date: 2022-07-08BEIHANG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2022-07-08

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Abstract

The invention relates to the technical field of air traffic management, and provides an airspace network capacity prediction method in severe weather. The method comprises the following steps: dividing an airport terminal area into a plurality of sub-airspaces according to a historical track, constructing a space-time diagram convolutional neural network diagram structure data set based on an attention mechanism according to a severe weather time list and a set number of node features, and designing and training the space-time diagram convolutional neural network based on the attention mechanism, the method comprises the following steps: acquiring a neural network parameter mapped by a weather-to-capacity influence mechanism, inputting graph structure feature data by using a trained time-space graph convolutional neural network based on an attention mechanism, and carrying out capacity prediction on each sub-airspace of an airspace network. According to the method, the airspace network capacity is predicted more accurately, the decision quality and the refinement degree are improved, meanwhile, the interpretability of the model is improved, the model is closer to the manual control judgment effect of a controller, and the control pressure of an air traffic control department is effectively relieved.
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Description

technical field

[0001] The invention relates to the technical field of air traffic management, in particular to a method for predicting airspace network capacity under bad weather. Background technique

[0002] In all kinds of flight abnormalities, severe weather is one of the main factors that prevent the normal operation of the flight, and its impact on the normal operation of the flight is reflected in the fact that the affected sectors and airport capacity are limited by the control department under severe weather, resulting in Affected by the flow control, flights were delayed or cancelled on a large scale, which eventually resulted in a large number of passengers stranded at the airport. Civil aviation takes passenger experience as the core. In order to avoid the occurrence of passengers stranded at the airport, it is necessary to predict the airspace capacity affected by bad weather in advance, so as to plan a new flight plan or cancel the flight, and release the info...

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Embodiment Construction

[0051] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are set forth in order to provide a thorough understanding of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0052] A method for predicting airspace network capacity under severe weather according to the present invention will be described in detail below with reference to the accompanying drawings.

[0053] figure 1 It is a flow chart of a method for predicting airspace network capacity under severe weather provided by the present invention.

[0054] figure 2 It is a schem...