Random forest-based airspace sector congestion degree prediction method

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...

AI Technical Summary

Problems solved by technology

At present, the prediction of air traffic congestion in my country is still in its infancy, and there is a lack of relevant research, and there is a lack of specific application methods.

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