Controlled airspace strategic flow prediction method based on gray long-short-term memory network

Abstract

The invention discloses a controlled airspace strategic flow prediction method based on a gray long-short-term memory network, and belongs to the technical field of air traffic flow management. The controlled airspace strategic flow prediction method comprises the following steps: step 1, reading data; step 2, preprocessing the data; step 3, preliminarily screening influence factors by utilizing grey correlation analysis; step 4, extracting main characteristics by utilizing a principal component analysis method; step 5, establishing a gray strategic flow prediction model; step 6, establishinga long short-term memory network strategic flow prediction model; and step 7, establishing a gray long-short-term memory network combination prediction model. For the controlled airspace strategic flow prediction method, scientific basis can be provided for airspace structure optimization such as sector division and route adjustment of the control area; effective utilization of airspace resourcesis achieved; and a basis is provided for resource demand distribution such as future personnel investment, financial investment and fixed asset investment of the controlled area.

Description

technical field [0001] The invention relates to a gray long-short-term memory network-based strategic flow prediction method in controlled airspace, which belongs to the technical field of air traffic flow management. Background technique [0002] In recent years, my country's civil aviation industry has developed rapidly, and the demand for air transportation has gradually become stronger. At present, my country's air traffic flow management service has been in a lagging and inefficient state, and the contradiction between it and the high-speed growth of air traffic flow has become increasingly prominent. Unreasonable airspace planning, low level of systematization and automation of flow management, low support capability of air traffic control system, and randomness of flow control make it difficult for existing airspace resources and management methods to adapt to the rapid growth of air traffic flow. Traffic congestion and flight conflicts in areas and airway intersecti...

AI Technical Summary

Problems solved by technology

At present, my country's air traffic flow management service has been in a lagging and inefficient state, and the contradiction between the rapid growth of air traffic flow has become increasingly prominent

Unreasonable airspace planning, low level of systematization and automation of flow management, low support capability of air traffic control system, and randomness of flow control make it difficult for existing airspace resources and management methods to adapt to the rapid growth of air traffic flow. Traffic congestion and flight conflicts in areas and airway intersections have formed a "bottleneck" in the air traffic network, which has also directly led to ground waiting before flight, air waiting, diversion, and yaw during flight. Thus affecting flight safety, increasing flight fuel consumption, and reducing flight regularity

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