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The influence of aggregation level and category construction on estimation quality for freight trip generation models

机译:集合水平和类别构造对货运行程生成模型估计质量的影响

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摘要

This paper analyzes the impacts of aggregation level and category construction on the relevance and quality of freight trip generation (FTG) models. More precisely, constant generations and functional form models are compared, as well as activity and activity-workforce categories. The paper proposes a method to compare constant generation and functional form models on different category classifications based on MAPE estimations. Functional forms are assessed via linear regression and compared using Pearson coefficient. Results show that the aggregation level has not always a positive impact on the model's accuracy and the choice of suitable functional form leads to more accurate models.
机译:本文分析了聚合水平和类别构建对货运行程生成(FTG)模型的相关性和质量的影响。更准确地说,将比较恒定代和功能形式模型,以及活动和活动劳动力类别。本文提出了一种基于MAPE估计来比较不同类别分类下的常量生成模型和函数形式模型的方法。通过线性回归评估功能形式,并使用皮尔森系数进行比较。结果表明,聚合水平并不总是对模型的准确性产生积极的影响,选择合适的函数形式可以使模型更准确。

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