Long-term and short-term memory neural network based flight delay grading early warning method

A long-short-term memory and flight delay technology, applied in biological neural network models, aircraft traffic control, instruments, etc., can solve problems such as model parameter data misleading, flight delays, and downstream flights and airports, achieving high prediction accuracy, Simple training with applicability
CN109448445AInactive Publication Date: 2019-03-08NANJING UNIV OF AERONAUTICS & ASTRONAUTICS

Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
Publication Date
2019-03-08
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses a long-term and short-term memory neural network based flight delay grading early warning method. The method includes analyzing an aviation meteorological message so that aviation meteorological data required by flight delay prediction can be obtained; performing multi-source data fusion to form an initial flight delay data set; converting non-numerical data into numericaldata by using semantic transformation, performing grading prediction on delay characteristics, and performing discrete partition on type characteristics and weather characteristics; performing data cleaning, missing value complementing and normalized processing to form a flight delay grading prediction standard data set, and performing partition; training long-term and short-term memory neural network based flight delay grading prediction models in batches on a training set; obtaining a long-term and short-term memory neural network model having the optimal hyperparameter on a verification set; performing verification on the performance of the optimal flight delay grading prediction model on a test set; and determining a delay early warning grade according to obtained flight delay grades through prediction. The method can effectively enhance the accuracy and reliability of flight delay early warning.
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Description

technical field

[0001] The invention belongs to the technical field of early warning methods for flight delays at airports, in particular to a hierarchical early warning method for flight delays based on long-short-term memory neural networks. Background technique

[0002] With the sustained, rapid and healthy development of the national economy, the demand for air transport is also increasing. However, in recent years, the phenomenon of large-scale flight delays has become increasingly prominent, and has become a worldwide problem that plagues civil aviation departments and passengers. Vicious incidents such as passengers refusing to board the plane, bullying the plane, attacking the airport, and beating staff due to flight delays are common occurrences, which have damaged the image of civil aviation's high-quality service and seriously affected the safe operation order of the airport. In order to reduce the delays caused by the airlines themselves, especially the improper...

Claims

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