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The Update of the Parameters in Activity-Based Simulation by Assimilation into Mobile Spatial Statistics

机译：通过吸收到移动空间统计中的基于活动的仿真中的参数更新

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The activity-based model (ABM) has been employed to forecast travel demand forecasting. However, this approach has significant shortcomings: the controversy over its alternative specific constant (ASC)'s temporal stability. To enhance such stability, various studies have tested different methods to update ASC. In this study, we propose another method of such an update that applies big data to the ABM-based simulation. This is to assimilate activity simulation to mobile spatial statistics (MSS), an estimated population data recorded by the of mobile phone connection. Because MSS can be estimated longitudinally, we can see the temporal variation of the ASC. In the empirical test, we reduced at least by 25% the distance between the number of people staying in the zone by the ABM simulation and the number of people staying in the zone of MSS.
机译：基于活动的模型（ABM）已用于预测旅行需求预测。但是，这种方法有很大的缺点：关于其替代比常数（ASC）的时间稳定性的争论。为了增强这种稳定性，各种研究已经测试了更新ASC的不同方法。在这项研究中，我们提出了另一种更新方法，将大数据应用于基于ABM的模拟。这是为了将活动模拟同化到移动空间统计（MSS），移动空间统计是由移动电话连接记录的估计人口数据。由于可以纵向估算MSS，因此我们可以看到ASC的时间变化。在经验检验中，我们通过ABM模拟将居住在该区域的人数与居住在MSS区域的人数之间的距离至少减少了25％。

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