一种基于多源大数据的城市停车分区方法及分区系统

• Format: Patent
• Language: Chinese
• Published: 22.11.2024
• Subjects: CALCULATING; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SIGNALLING; TRAFFIC CONTROL SYSTEMS

本发明提供一种基于多源大数据的城市停车分区方法及分区系统，首先确定停车分区的研究主体与分区对象，并将各类数据集计到交通小区上；其次通过相关性分析识别有效的数据特征维度，完成数据维度筛选；然后采用加权改进的K-均值聚类算法识别交通小区所属的聚类，并采用凝聚聚类算法合并相似聚类；最后利用路网、行政边界构造停车分区，将交通小区的聚类属性映射其上，从而获得具备分区属性的、实操性强的停车分区。该分区方法及分区系统可求解多种应用场景下的城市停车分区，其科学性、合理性、求解效率、可实施性高，可以为城市停车分区的差异化管理提供技术支撑。 The invention provides an urban parking zoning method and zoning system based on multi-source big data, and the method comprises the steps: firstly determining a research subject and a zoning object of parking zoning, and enabling various data sets to be recorded on a traffic zone; secondly, effective data feature dimensions are identified through correlation analysis, and data dimension screening is completed; then, a weighted improved K-means clustering algorithm is adopted to identify clusters to which the traffic cells belong, and a condensation clustering algorithm is adopted to merge similar clusters; and finally, constructing a parking zone by using a road network and an administrative boundary, and mapping the clustering attribute of the traf