【摘要】 针对部分机场历史运行数据样本不服从高斯分布的特点，在原有评估方法和行业运行规范的基础上，提出了基于正态转换的机场高峰服务能力评估方法。通过对历史运行数据的预处理，统计得到了小时进离场架次数值，并引入新变量欧式距离代替进离场架次数值作为评估的数据样本。分别采用Box-Cox转换、Johnson转换等方法对非正态样本数据进行正态转换，并利用正态特性完成基于统计区间的高峰服务能力评估。以武汉机场为例，计算并比较了不同方法的评估结果与机场参考容量的偏差。结果表明：方法可以有效提升评估结果准确度，摆脱了样本数据分布特性对评估结果的影响。更多还原

【Abstract】 In view of the fact that some airport historical operation data do not obey the Gaussian distribution, an airport peak service capability evaluation method based on normality transformation was proposed on the basis of the original evaluation methods and industry operation specification.By preprocessing the historical data, the hourly arrivals and departures were statistically obtained, and a new variable, Euclidean distance, was introduced to replace the arrivals and departures as the data sample for evaluation.The Box-Cox transformation and Johnson transformation were used to convert the non-normal data, and the normal characteristics were used to complete the evaluation based on statistical interval.Taking Wuhan Airport as an example, the deviation between the evaluation results of different methods and the reference capacity of the airport is calculated and compared.The results show that the proposed method can effectively improve the accuracy of evaluation and get rid of the influence of data distribution characteristics on evaluation results.更多还原