Flight delays may be decreased in a predictable way if the Weibull wind speed parameters of a runway, which are an important aspect of safety during the take-off and landing phases of aircraft, can be determined. One aim of this work is to determine the wind profile of Hasan Polatkan Airport (HPA) as a case study. Numerical methods for Weibull parameter determination perform better when the average wind speed estimation is the main objective. In this paper, a novel objective function that minimises the root-mean-square error by employing the cumulative distribution function is proposed based on the genetic algorithm and particle swarm optimisation. The results are compared with well-known numerical methods, such as maximum-likelihood estimation, the empirical method, the graphical method and the equivalent energy method, as well as the available objective function. Various statistical tests in the literature are applied, such as R2, Root-Mean-Square Error (RMSE) and $\chi$2. In addition, the Mean Absolute Error (MAE) and total elapsed time calculated using the algorithms are compared. According to the results of the statistical tests, the proposed methods outperform others, achieving scores as high as 0.9789 and 0.9996 for the R2 test, as low as 0.0058 and 0.0057 for the RMSE test, 0.0036 and 0.0045 for the MAE test and 3.53 × 10−5 and 3.50 × 10−5 for the $\chi$2 test. In addition, the determination of the wind speed characteristics at HPA show that low wind speed characteristics and regimes throughout the year offer safer take-off and landing schedules for target aircraft. The principle aim of this paper is to help establish the correct orientation of new runways at HPA and maximise the capacity of the airport by minimising flight delays, which represent a significant impediment to air traffic flow.

中文翻译：

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估计风速数据威布尔参数的元启发式数据拟合方法：以哈桑波拉特坎机场为例

如果可以确定作为飞机起飞和着陆阶段安全的重要方面的跑道的 Weibull 风速参数，则可以以可预测的方式减少航班延误。这项工作的一个目的是确定哈桑波拉特坎机场 (HPA) 的风廓线作为案例研究。当平均风速估计是主要目标时，威布尔参数确定的数值方法表现更好。在本文中，基于遗传算法和粒子群优化，提出了一种利用累积分布函数最小化均方根误差的新目标函数。将结果与众所周知的数值方法进行比较，例如最大似然估计、经验法、图解法和等效能量法，以及可用的目标函数。应用了文献中的各种统计检验，例如R2, 均方根误差 (RMSE) 和$\chi$2. 此外，还比较了使用算法计算的平均绝对误差 (MAE) 和总经过时间。根据统计测试的结果，所提出的方法优于其他方法，得分高达 0.9789 和 0.9996R2测试，RMSE 测试低至 0.0058 和 0.0057，MAE 测试低至 0.0036 和 0.0045，3.53 × 10-5和 3.50 × 10-5为了$\chi$2测试。此外，HPA 风速特性的测定表明，全年的低风速特性和风态为目标飞机提供了更安全的起飞和着陆时间表。本文的主要目的是帮助建立 HPA 新跑道的正确方向，并通过最大限度地减少航班延误来最大限度地提高机场容量，这对空中交通流量来说是一个重大障碍。