Purpose

The purpose of this study is to describe precisely the wind speed regime and characteristics of a runway of an International Airport, the north-western part of Turkey.

Design methodology approach

Three different probability distributions, namely, Inverse Gaussian (IG), widely used two-parameter Weibull and Rayleigh distributions in the literature, are used to represent wind regime and characteristics of the runway. The parameters of each distribution are estimated by the pattern search (PS)-based heuristic algorithm. The results are compared with the other three methods-based numerical computation, including maximum-likelihood method, moment method (MoM) and power density method, respectively. To evaluate the fitting performance of the proposed method, several statistical goodness tests including the mostly used root mean square error (RMSE) and chi-squared (X²) are conducted.

Findings

In the light of the statistical goodness tests, the results of the IG-based PS attain better performance than the classical Weibull and Rayleigh functions. Both the RMSE and X² values achieved by the IG-based PS method lower than that of Weibull and Rayleigh distributions. It exhibits a better fitting performance with 0.0074 for RMSE and 0.58 × 10⁻⁴ for X² for probability density function (PDF) in 2012 and with RMSE of 0.0084 and X² of 0.74 × 10⁻⁴ for PDF in 2013. As regard the cumulative density function of the measured wind data, the best results are found to be Weibull-based PS with RMSE of 0.0175 and X² of 3.25 × 10⁻⁴ in 2012. However, Weibull-based MoM shows more excellent ability in 2013, with RMSE of 0.0166 and X² of 2.94 × 10⁻⁴. Consequently, it is considered that the results of this study confirm that IG-based PS with the lowest error value can a good choice to model more accurately and characterize the wind speed profile of the airport.

Practical implications

This paper presents a realistic point of view regarding the wind regime and characteristics of an airport. This study may cast the light on researchers, policymakers, policy analysts and airport designers intending to investigate the wind profile of a runway at the airport in the world and also provide a significant pathway on how to determine the wind distribution of the runway.

Originality value

Instead of the well-known Weibull distribution for the representing of wind distribution in the literature, in this paper, IG distribution is used. Furthermore, the suitability of IG to represent the wind distribution is validated when compared with two-parameter Weibull and Rayleigh distributions. Besides, the performance and efficiency of PS have been evaluated by comparing it with other methods.

中文翻译：

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基于概率的跑道风分布确定分析

目的

这项研究的目的是精确描述土耳其西北部国际机场的风速状况和跑道特征。

设计方法论方法

三种不同的概率分布，即逆高斯（IG），是文献中广泛使用的两参数Weibull和Rayleigh分布，用于表示风况和跑道的特征。通过基于模式搜索（PS）的启发式算法估计每个分布的参数。将结果与其他三种基于方法的数值计算进行了比较，分别包括最大似然法，矩量法（MoM）和功率密度法。为了评估所提出方法的拟合性能，进行了一些统计优度检验，其中包括最常用的均方根误差（RMSE）和卡方（X ²）。

发现

根据统计优度检验，基于IG的PS的结果比经典的Weibull和Rayleigh函数具有更好的性能。通过基于IG的PS方法获得的RMSE和X ²值均低于Weibull和Rayleigh分布。它显示出更好的拟合性能0.0074为RMSE和0.58×10 ^-4为X ²为概率密度函数（PDF）在2012年和与0.0084 RMSE和X ²为0.74×10 ^-4在2013年作为PDF都把累积的风函数密度函数，发现最好的结果是基于威布尔的PS，RMSE为0.0175，X ²为3.25×102012年为⁻⁴。然而，基于威布尔的MoM在2013年显示出更出色的能力，RMSE为0.0166，X ²为2.94×10 ^-4。因此，可以认为，这项研究的结果证实了误差值最低的基于IG的PS可以成为更好地建模和表征机场风速分布的良好选择。

实际影响

本文提出了关于机场的风况和特性的现实观点。这项研究可能会为打算研究世界机场跑道风廓线的研究人员，政策制定者，政策分析师和机场设计师提供启示，也为确定跑道风向提供重要途径。

创意价值

在本文中，使用IG分布代替文献中众所周知的用于表示风分布的Weibull分布。此外，与两参数威布尔分布和瑞利分布相比，IG代表风分布的适用性得到了验证。此外，通过与其他方法进行比较，对PS的性能和效率进行了评估。