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Origin-Destination Distribution Prediction Model for Public Bicycles Based on Rental Characteristics

机译:基于租赁特征的公共自行车原始目的地分布预测模型

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Accurate prediction of the rental demand origin-destination distribution of public bicycles provides a foundation according to which layout planning, operational management and dispatching of bicycle sharing system stations may be achieved. Based on the conventional double-constrained gravity model, the rental duration distribution function was employed as a distribution impedance function in order to establish a prediction model for the origin-destination distribution of public bicycles in a bicycle sharing system. The expense incurred by the weighted average travel time of the bicycle sharing system located in the old town of Zhenhai District, Ningbo, was applied to test the origin-destination distribution prediction model for public bicycles based on characteristics of rental duration distribution. Results indicate that the established model demonstrates high precision and can be used to effectively predict the origin-destination distribution of bicycle sharing systems, thus avoiding the dense distribution over short distances which results from the conventional double-constrained gravity model.
机译:准确预测租赁需求的起源目的地公共自行车的目的地分配提供了一个基础,根据该职位,可以实现自行车共享系统站的布局规划,运营管理和调度。基于传统的双约束重力模型,租金持续时间分布函数被用作分配阻抗函数,以便为自行车共享系统中公共自行车的原始目的地分布建立预测模型。宁波镇海区老镇的自行车共享系统加权平均旅行时间产生的费用被应用于基于租金持续时间分布特征来测试公共自行车的原始目的地分布预测模型。结果表明,所建立的模型表现出高精度,并且可以用来有效地预测自行车共享系统的起源目的地分布,从而避免了传统的双限制重力模型的短距离的密集分布。

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