Flight delay affection prediction method and system based on fuzzy Petri network

A technology of flight delay and prediction method, applied in the field of flight information processing and deep learning, can solve the problems of weak adaptability, many related factors, and many variables, and achieve the effect of making up for interpretability and robustness

Active Publication Date: 2022-01-07
武汉市胜意科技发展有限公司
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the prior art, the fuzzy Petri net is used to predict flight delays. The methods involved in the method involve many variables and many related factors, which leads to poor actual adaptability and cannot meet the needs of flight delays caused by changes in weather factors, flow control and company management in real time.

Method used

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  • Flight delay affection prediction method and system based on fuzzy Petri network
  • Flight delay affection prediction method and system based on fuzzy Petri network
  • Flight delay affection prediction method and system based on fuzzy Petri network

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Embodiment 2

[0037] refer to Figure 5 , a second aspect of the present invention provides a fuzzy Petri net-based flight delay spread prediction system 1, comprising: an acquisition module 11, used to acquire the flight information of one or more target flights that have been delayed, the flight information Including flight number, airline, airport of departure and airport of arrival; building block 12, used to construct the flight network and airport network affected by each delayed flight according to the historical flight information and fuzzy Petri net of multiple delayed flights; determine Module 13 is used to utilize the trained spatio-temporal graph convolutional neural network to determine the delay duration prediction of each target flight; module 14 is used to determine the delay duration of each target flight and the future weather information within the delay duration With the fuzzy Petri net, all affected flights of each target flight are predicted in real time.

[0038] Fur...

Embodiment 3

[0040] refer to Figure 6 , the third aspect of the present invention provides an electronic device, including: one or more processors; storage means for storing one or more programs, when the one or more programs are used by the one or more executed by one or more processors, so that the one or more processors implement the method of the first aspect of the present invention.

[0041] The electronic device 500 may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 501, which may be loaded into a random access memory (RAM) 503 according to a program stored in a read-only memory (ROM) 502 or loaded from a storage device 508 Various appropriate actions and processing are performed by the program. In the RAM 503, various programs and data necessary for the operation of the electronic device 500 are also stored. The processing device 501 , ROM 502 and RAM 503 are connected to each other through a bus 504 . An input / output (I / O) int...

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Abstract

The invention relates to a flight delay affection prediction method and system based on a fuzzy Petri network, and the method comprises the steps: obtaining the flight information of one or more delayed target flights, wherein the flight information comprises a flight number, an airline company, a departure place airport and an arrival place airport; constructing a flight network and an airport network accompanied by each delayed flight according to the historical flight information of the plurality of delayed flights and the fuzzy Petri network; determining the delay duration of each target flight by using the trained space-time diagram convolutional neural network; and according to the delay duration of each target flight, the future weather information in the delay duration and the fuzzy Petri network, predicting all affected flights of each target flight in real time. According to the method and system, the fuzzy Petri network and the space-time diagram convolutional neural network are combined, and the real-time performance and the dynamic adaptability of flight delay prediction of the fuzzy Petri network are improved.

Description

technical field [0001] The invention belongs to the technical field of flight information processing and deep learning, and in particular relates to a fuzzy Petri net-based prediction method and system for flight delay and impact. Background technique [0002] In recent years, with the development of my country's economy and the steady increase of comprehensive national strength, my country's civil aviation industry has been developing steadily, and the international status of civil aviation industry is also gradually improving. With the continuous growth of my country's air traffic volume, the airspace capacity tends to be saturated, and the imbalance between airspace capacity and flow is becoming more and more serious. If there are emergencies such as bad weather or air traffic control, it will cause large-scale flight delays. It has seriously affected the travel plans of passengers, and has also brought huge economic losses to airlines and society. [0003] According to r...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06N5/04G06N3/08G06N3/04G06Q50/30
CPCG06Q10/04G06Q50/30G06N5/048G06N3/08G06N3/045
Inventor 余学锋刘洁
Owner 武汉市胜意科技发展有限公司
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