Transactions of Nanjing University of Aeronautics & Astronautics
Forecast of Air Traffic Controller Demand Based on SVR and Parameter Optimization
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Abstract:
As the main body of air traffic control safety， the air traffic controller is an important part of the whole air traffic control system. According to the relevant data of civil aviation over the years， a mapping model between flight support sorties and air traffic controller demand is constructed by using the prediction algorithm of support vector regression （SVR） based on grid search and cross-validation. Then the model predicts the demand for air traffic controllers in seven regions. Additionally， according to the employment data of civil aviation universities， the future training scale of air traffic controller is predicted. The forecast results show that the average relative error of the number of controllers predicted by the algorithm is 1.73%， and the prediction accuracy is higher than traditional regression algorithms. Under the influence of the epidemic， the demand for air traffic controllers will decrease in the short term，but with the control of the epidemic，the demand of air traffic controllers will return to the pre-epidemic level and gradually increase. It is expected that the controller increment will be about 816 by 2028. The forecast results of the demand for air traffic controllers provide a theoretical basis for the introduction and training of medium and long-term air traffic controllers， and also provide method guidance and decision support for the establishment of professional reserve and dynamic control mechanism in the air traffic control system.
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This work was supported by the National Natural Science Foundation of China（No.71971114）.
Clc Number:
C961
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