Continuous model of two-stage method

Abstract

The invention discloses a continuous model of a two-stage method. The first-stage frequency analysis is used for detecting periodicity in the data. In the second stage, statistical analysis is carriedout to confirm the mode detected in the first stage and determine factors related to delay. A plurality of logistic regression and binary logistic regression models are established to check the influence of various factors on average daily delay and single flight delay, and the method aims to evaluate the punctual arrival ability of an aircraft and identify flight delay by using an innovative two-stage method. According to the method, a new mathematical algorithm is used, and the phenomenon of periodic repetition can be identified in flight delay, that is, the periodic flight delay characteristic is achieved. Based on the detected recurrence phenomenon, an important variable affecting the delay may be identified. The relationship between the variables and flight delay is researched by using a statistical technology. According to the method, the flight delay trend can be displayed, and airport management personnel can be helped to formulate an effective strategy for reducing flight delay.

Description

technical field [0001] The invention relates to the field of aviation technology, in particular to a continuous model of a two-stage method. Background technique [0002] Relevant scholars at home and abroad have carried out a lot of research on the problem of flight delay prediction. Most of the existing methods use machine learning algorithms such as decision trees, Bayesian networks, and neural networks. Some researchers have found that delays are caused by inadequate air traffic control and irregular air operations; for example, studies have found that most delays at European airports are related to difficulties with air traffic control. Likewise, Mueller and Chatterji suggested that the reason for the delay was related to changes in the airline's operating and management procedures. In this regard, the study found that delays in flight schedules are inherently due to limited operations between flights and random disruptions in air operations. The increased number of s...

AI Technical Summary

Problems solved by technology

Studies have shown that nearly 75% of systems experience delays due to adverse weather conditions, primarily due to reduced airport capacity due to increased separation of aircraft during adverse weather conditions

In particular, severe weather such as high surface winds and low visibility make it difficult for aircraft to land, which increases arrival delays

For similar reasons, based on prevalent summer fog and winter rainstorms, and increased arrival delays at San Francisco airport

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