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Forecasting a Global Air Passenger Demand Network Using Weighted Similarity-Based Algorithms

机译:基于加权相似度算法的全球航空客运需求网络预测

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The aim of this study is to define an appropriate approach to forecast the appearance and disappearance of air passenger demand between cities worldwide. For the 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 is 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:这项研究的目的是定义一种适当的方法来预测全球各城市之间航空客运需求的出现和消失。对于航空客运需求链接的预测,使用了基于加权相似度的算法,并分析了九个指标。加权资源分配指数显示出最佳指标。通过比较三个不同年份的建模数据和已知数据,确定了此方法的准确性。应用基于相似性的算法时,已知数据用于建立边界。结果,发现应将具有定义边界的加权资源分配索引用于航空客运需求网络中的链路预测。此外,结果表明,根据社会经济指标对航空客运需求网络内的城市进行分组可以提高预测的准确性。

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