A method and system for error correction and correction of aviation messages based on deep learning

Abstract

The present invention discloses a method and system for error correction and correction of aviation messages based on deep learning, comprising: receiving a pilot plan report, analyzing the pilot plan report, and obtaining route information to be verified; using a pre-established route-frequency dictionary And the pre-trained error detection depth model judges whether there is an error in the route information to be verified, and then uses the pre-trained error correction depth model and correction model to correct the error route information. This method ensures that the output FPL message contains correct route information through the multiple verification and correction mechanisms of the frequency dictionary, error detection model, error correction model, and correction model. This method can realize the FPL message (pilot plan report) Automatic analysis, including error detection and correction for route formation, ensures the accuracy of the output FPL message and reduces the pressure on air traffic control.

Description

A method and system for error correction and correction of aviation messages based on deep learning technical field The present invention relates to the technical field of air traffic information management, in particular to a kind of aviation report based on deep learning. A text error correction method and system. Background technique [0002] The sending and receiving of dynamic fixed-format telegrams of civil aviation are important for each air traffic control unit and aviation company. It is one of the important means for the flight department to understand and master the flight dynamics. The specification, correct use of telegrams is not only about flight dynamics The basis for timely and accurate transmission of information is also an important guarantee for air traffic safety, order and efficiency. pilot plan report (FPL) is the most frequent message of all messages and is issued by the air traffic services unit according to the aircraft operator or agent in ...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to overcome the problems in the prior art that pilot plan reports are written and issued manually, are prone to errors, and interfere with aviation control work, and provide a method and system for error correction and correction of aviation messages based on deep learning. It can realize automatic analysis of FPL messages, including error detection and error correction of route formation, to ensure the accuracy of output FPL messages and reduce the pressure of air traffic control

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