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基于滚动时域算法的航班滑行路径优化模型 总被引:1,自引:0,他引:1
为了提高机场场面运行效率和机场空侧容量,亟需采取积极的手段对滑行路径进行优化。根据滑行路径规划的问题属性,选取离场航班为研究对象,建立了以滑行时间最短为目标函数的无冲突滑行路径优化模型,并设计了基于滚动时域与混合整数线性规划(MILP)相结合的迭代算法;将滑行路径优化模型植入空域管理与评估系统(ACES)的空侧容量评估系统中,以杭州萧山国际机场场面数据为例,对不同策略下的航班滑行时间、容量评估结果及路径更改次数进行了比较分析,验证了模型的准确性,通过比较MILP与新算法下的计算时间验证了算法的高效性。 相似文献
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Chaotic characteristics of traffic flow time series is analyzed to further investigate nonlinear characteristics of air traffic system. Phase space is reconstructed both by time delay which is built through mutual information, and by embedding dimension which is based on false nearest neighbors method. In order to analyze chaotic characteristics of time series, correlation dimensions and the largest Lyapunov exponents are calculated through Grassberger-Procaccia (G-P) algorithm and small-data method. Five-day radar data from the control center in Guangzhou area are analyzed and the results show that saturated correlation dimensions with self-similar structures exist in time series, and the largest Lyapunov exponents are all equal to zero and not sensitive to initial conditions. Air traffic system is affected hy multiple factors, containing inherent randomness, which lead to chaos. Only grasping chaotic characteristics can air traffic be predicted and controlled accurately. 相似文献
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