中文摘要：

分析公交客流规模的关联因素，梳理与公交客流规模有关的关联规则，有助于决策者把握整体态势、定义现状问题、细分问题类型。本文以深圳市为案例，以交通小区为分析单元，基于公交IC卡数据、人口数据、兴趣点数据、电子地图路径规划数据、微博签到数据等多源数据，从建成环境、人口密度、公交线网设施、交通可达性等维度，定量地表现影响公交客流规模的关联因素。通过构建决策树模型，揭示公交客流规模与关联因素间的映射关系，提取与公交客流规模有关的关联规则。研究结论为基于多源数据的公交客流规模评价方法提供了一种新的思路，也为公交线网规划提供了决策支持工具。

英文摘要：

To understand key factors associated bus passenger volume can help decision makers to have an overall knowledge of current situation and properly propose existing problems. This paper took Shenzhen as a case and analyzed on transportation analysis zone level. Several factors are assumed to associate with bus passenger volume, including built environment, population density, transit accessibility, bus network density and metro-bus connection, which can be characterized through bus smart card data, population data, POI data, path planning data, Weibo check- in data and GIS data. Based on these indexes, decision trees are built to show mapping relationships and association rules between bus passenger volume and other indexes. Conclusions can be drawn that this research not only offers a new evaluation method for bus passenger volume, but also can support bus line network planning.