Flight delay real-time probability prediction method based on Bayesian network algorithm

Abstract

The invention discloses a flight delay real-time probability prediction method based on a Bayesian network algorithm, and the method comprises the steps: formulating a flight delay judgment standard,analyzing a delay wave and the impact on flight delay, and determining the release fairness of departure flights; analyzing the delay characteristics, determining flight delay factors, and creating aflight delay dynamic prediction model based on a Bayesian network; adopting a dynamic prediction technology based on a time sequence to predict the present transverse wave and measurement index to obtain a final flight delay prediction value, and generating a prediction set; and carrying out probability prediction on prediction set data by utilizing the flight delay dynamic prediction model obtained by training, and obtaining a prediction value of each flight delay level by adopting a probability maximum principle. According to the invention, real-time probability prediction can be carried outon the departure delay level of a single flight of an airport every day, the flight delay prediction precision is improved, a delay early warning notice is issued to passengers in time, an operationstrategy is adjusted in time, and various adverse effects caused by flight delay are reduced.

Description

technical field [0001] The invention relates to the technical field of flight delay prediction, in particular to a real-time probability prediction method of flight delay based on a Bayesian network algorithm. Background technique [0002] With the rapid development of my country's air transport industry, the number of flights has increased significantly, and at the same time, frequent flight delays have become a major problem in airport operation and management. The problem of flight delays has not only become a travel problem for the majority of passengers, but also caused huge time and cost losses to airlines and airports. In order to minimize costs and maximize resource utilization, airlines arrange flight schedules more compactly. This makes flight delays likely to cause a chain reaction, which will affect more downstream flights and airports, resulting in problems such as stranded passengers and unbalanced allocation of resources between airports and airlines. If rel...

AI Technical Summary

Problems solved by technology

Although the invention uses a Bayesian classifier to create a flight delay prediction model, there are still the following problems: First, the data basis of the model is the flight delay data after dimensionality reduction processing. The key parameter characteristics in the flight delay data selected by the method, the prediction accuracy is not high, the second, the present invention is to carry out simple two-category prediction for whether a single flight is delayed, or carry out deterministic single classification for the delay time or delay level of a single flight. Value prediction is not considered in consideration of the airport as a whole, which is less helpful to the overall scheduling of the airport and has low practicability

Third, the ability to adapt to temporary emergencies (such as sudden weather problems) is low, resulting in a large drop in forecasting accuracy in some cases

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