Random forest-based airspace sector congestion degree prediction method

A technology of airspace sectors and congestion levels, applied in traffic flow detection, traffic control systems of road vehicles, instruments, etc., can solve problems such as lack of application methods and lack of research, and achieve scientific and reasonable prediction results

Active Publication Date: 2019-03-08
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

At present, the prediction of air traffic congestion in my country is still in its infancy, a

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  • Random forest-based airspace sector congestion degree prediction method
  • Random forest-based airspace sector congestion degree prediction method
  • Random forest-based airspace sector congestion degree prediction method

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[0045] The present invention will be described in detail below with reference to the drawings and embodiments:

[0046] Such as figure 1 As shown, the method for predicting the degree of congestion in airspace sectors based on random forest includes the following steps:

[0047] (1) Read in historical data: process sector trajectory data (using a sector’s 1-week data for experiments), and calculate the week, time period, sector capacity saturation, number of potential conflicts, sector aircraft density, sector The seven indicators of regional aircraft average speed saturation and sectoral aircraft average distance are arranged from left to right to form the index name of the first row of the data set. The data of the latter five indicators are one-to-one corresponding to the week and time period to obtain the daily The sector in each time period contains a data set of five index data including sector capacity saturation, number of potential conflicts, sector aircraft density, sect...

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Abstract

The invention discloses a random forest-based airspace sector congestion degree prediction method and belongs to the field of air traffic congestion degree prediction. With the method adopted, the congestion degree of an airspace sector can be predicted scientifically and reasonably. The method of the invention includes following five steps of: reading historical data; preprocessing data; constructing a feature set; constructing a decision tree; and predicting the congestion level of the sector by using the random forest. According to the method, the five indicators, namely, sector capacity saturation, potential conflict number, sector aircraft density, sector aircraft average speed saturation and sector aircraft average distance, are processed; a fuzzy evaluation method is used to obtaincongestion levels corresponding to each time segment of the sector; an ID3 algorithm is used as a core algorithm to construct the decision tree; and samples are drawn and substituted into the decisiontree; classification is carried out layer by layer, and a prediction result is obtained; and three kinds of evaluation index data, such as prediction accuracy, prediction average absolute error, andprediction average percentage error, are calculated according to the prediction result; and the average value of each indicator is obtained, an whether prediction is accurate can be evaluated.

Description

Technical field [0001] The invention belongs to the field of air traffic congestion degree prediction, and in particular relates to a method for predicting airspace sector congestion degree based on random forest. Background technique [0002] With the rapid development of air transportation business, under the condition of relatively limited airspace resources, traffic congestion is becoming more and more serious, which seriously affects the safety and efficiency of air traffic operations. Although domestic breakthroughs have been made in identifying the degree of air traffic congestion , But only recognition can no longer satisfy the current and future research on air traffic congestion. In the face of increasingly saturated airspace and mixed and diverse operation modes, how to accurately predict the degree of traffic congestion in airspace sectors and deploy corresponding traffic management measures in advance according to the forecast has become an urgent problem for air tra...

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Application Information

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IPC IPC(8): G08G1/01
CPCG08G1/0104G08G1/0125G08G1/0133
Inventor 曾维理孙煜时李杰何玉建赵子瑜羊钊胡明华
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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