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基于宁波市公共自行车刷卡数据、POI(Point of Interest)数据、气象和空气质量等数据,从数据驱动视角,深入挖掘公共自行车使用的时空特征及站点租还车需求预测。在时间上,采用KMeans算法,将站点聚为5类,探讨各类站点的时变需求规律及影响因素;在空间上,提出基于POI 数据的站点用地类型识别方法,将站点分为居住类、交通设施类、办公类和商业休闲类。构建以 15,30,60 min 为间隔,以租还车需求为目标变量的随机森林预测模型,并与常用的 BP (Back Propagation)神经网络、K最近邻方法进行比较。结果表明,随机森林模型的精度更高,适用性更强。以30 min为间隔的站点租还车需求预测精度最高,考虑站点土地利用类型后能有效提高模型的预测精度。本文结果可作为未来站点平衡调度的依据并推广应用于共享单车系统,为改善服务水平提供技术和理论支撑。 相似文献
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ABSTRACTThe economic history of the U.S. illustrates how the role of many cities has been changed by being seaports or located on navigable rivers or lakes. Based on the widening of the Panama Canal in 2016, the West Coast ports that include the west coast seaports of California, Oregon, and Washington were expected to become less important, while the freight shares of the East Coast and Gulf ports would increase. By how much it has been not easy to measure or predict so far, but this study attempted to define some of the key parameters in the measurement. As well as several relevant background topics, both the demand- and supply-side versions of the National Interstate Economic Model, have been applied for the measurement of economic impacts. U.S. port authorities and policy makers at the local and national levels who respond and develop plans for coping with the new realities of the Panama Canal are able to understand the extent to which changes in shippers’ and land-mode transporters’ behaviors would undermine the logistics and the costs of their activities. Therefore, this study is important for a diverse spectrum of port development strategies in the U.S. to respond to the Canal expansion. 相似文献
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《铁路技术管理规程》是我国铁路的基本规章,研究不同版本的演变特征对其管理及不断修订完善具有重要意义。通过对铁路列车提速以来近三版《铁路技术管理规程》修订背景回顾与发展历程分析,基于文本相似度算法,构建了不同版本间的条款关联关系并量化分析了相邻版本及各个章节条款关联强度。运用政策文献计量法,逐版逐条研究其修订类型并从版本与章节两个维度分别量化分析了条款修订类型分布特征。在此基础上,总结提出了《铁路技术管理规程》演变发展特征与趋势。该研究对《铁路技术管理规程》的科学管理及今后动态修订完善具有重要支撑作用。 相似文献
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ABSTRACTThe advent of the autonomous vehicle (AV) will affect not only the transportation system, but also future patterns of land development. Integrated land use and transportation models will be critical tools in assessing the path forward with this technology. Key questions with respect to land use impacts of AVs arise from potential changes in sensitivity to travel and reduced demand for parking. It is an open question whether AVs will induce urban sprawl, or whether spatial economies of agglomeration will mitigate any reductions in travel time sensitivity. The deployment of shared fleets of AVs would likely reduce parking demand, producing yet to be explored impacts on property development within existing urban footprints. We perform a critical assessment of currently operational models and their ability to represent the adoption of AVs. We identify the representation of time in such models as a vital component requiring additional development to model this new technology. Existing model applications have focused on the discrete addition of new infrastructure or policy at a fixed point in time, whereas AV adoption will occur incrementally through time. Stated adaptation surveys are recommended as tools to quantify preferences and develop relevant model inputs. It is argued that existing models that assume comparatively static equilibrium have been convenient in the past, but are insufficient to model technology adoption. In contrast, dynamic model frameworks lack sufficient structure to maintain reasonability under large perturbations from base conditions. The ongoing advancement of computing has allowed models to move away from being mechanistic aggregate tools, towards behaviourally rich depictions of individual persons and firms. However, much work remains to move from projections of existing conditions into the future, to the evolution of the spatial economy as it evolves through time in response to new technologies and exogenous stresses. Principles from complex and evolutionary systems theory will be important in the development of models with the capacity to consider such dynamics. 相似文献
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