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Forecasting global air passenger demand network using weighted similarity-based algorithms

机译:使用加权相似性算法预测全球空气乘客需求网络

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The aim of this study is to define an appropriate approach to forecast the appearance of the air passenger demand between cities worldwide. For air passenger demand link forecasting a weighted similarity-based algorithm is used, with an analysis of nine indices. The weighted resource allocation index demonstrates the best metrics. The accuracy of this method has been determined through a comparison of modeled and known data from three separate years. The known data was used to establish boundaries when applying the similarity-based algorithm. As a result, it was found that a weighted resource allocation index, with defined boundaries, should be utilized for link prediction in the air passenger demand network. Furthermore, it is shown that grouping cities within the air passenger demand network, based on socio-economic indicators, increases the accuracy of the forecast.
机译:本研究的目的是定义适当的方法,以预测全球城市之间的空气乘客需求的外观。对于空气乘客需求链路预测,使用加权相似性的算法,分析了九个指标。加权资源分配索引演示了最佳指标。通过从三个单独的年度的建模和已知数据的比较来确定该方法的准确性。在应用基于相似性的算法时,已知数据用于建立边界。结果,发现具有定义边界的加权资源分配索引应用于空中乘客需求网络中的链路预测。此外,表明,基于社会经济指标的空中客运需求网络中的分组城市提高了预测的准确性。

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