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Probabilistic Methods for Airspace Sector Congestion Prediction

机译:空域拥塞预测的概率方法

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Abstract-In order to improve the accuracy of airspace sector congestion prediction, the probabilistic method for sector congestion prediction has been proposed. By analyzing the uncertainty of air traffic, on the basis of theoretical analysis about sector demand probabilistic forecasting, the sector demand probabilistic forecasting method and the sector congestion prediction method based on the Monte Carlo simulation have been proposed. The methods are easy to implement. The simulation results show that the methods reduce the uncertainty of the previous demand forecasting and improve the accuracy of sector congestion prediction.
机译:摘要-为了提高空域扇区拥塞预测的准确性,提出了一种概率估计方法。通过分析空中交通流量的不确定性,在对部门需求概率预测进行理论分析的基础上,提出了基于蒙特卡洛模拟的部门需求概率预测方法和部门拥塞预测方法。该方法易于实现。仿真结果表明,该方法减少了先前需求预测的不确定性,提高了行业拥塞预测的准确性。

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