• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>ACM transactions on intelligent systems and technology >Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network
【24h】

Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network

机译：使用门控图神经网络动态规划Vockless公共自行车共用系统中的自行车站

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Benefiting from convenient cycling and flexible parking locations, the Dockless Public Bicycle-sharing (DL-PBS) network becomes increasingly popular in many countries. However, redundant and low-utility stations waste public urban space and maintenance costs of DL-PBS vendors. In this article, we propose a Bicycle Station Dynamic Planning (BSDP) system to dynamically provide the optimal bicycle station layout for the DL-PBS network. The BSDP system contains four modules: bicycle drop-off location clustering, bicycle-station graph modeling, bicycle-station location prediction, and bicycle-station layout recommendation. In the bicycle drop-off location clustering module, candidate bicycle stations are clustered from each spatio-temporal subset of the large-scale cycling trajectory records. In the bicycle-station graph modeling module, a weighted digraph model is built based on the clustering results and inferior stations with low station revenue and utility are filtered. Then, graph models across time periods are combined to create a graph sequence model. In the bicycle-station location prediction module, the GGNN model is used to train the graph sequence data and dynamically predict bicycle stations in the next period. In the bicycle-station layout recommendation module, the predicted bicycle stations are fine-tuned according to the government urban management plan, which ensures that the recommended station layout is conducive to city management, vendor revenue, and user convenience. Experiments on actual DL-PBS networks verify the effectiveness, accuracy, and feasibility of the proposed BSDP system.
机译：从方便的骑自行车和灵活的停车位置受益，无轨公共自行车共享（DL-PBS）网络在许多国家变得越来越受欢迎。然而，冗余和低实用电台废物公共城市空间和DL-PBS供应商的维护成本。在本文中，我们提出了一辆自行车站动态规划（BSDP）系统，以动态为DL-PBS网络提供最佳自行车站布局。 BSDP系统包含四个模块：自行车掉落位置聚类，自行车站图建模，自行车站定位预测和自行车站布局推荐。在自行车脱落位置聚类模块中，候选自行车站从大规模循环轨迹记录的每个时空子集中聚集。在自行车站图建模模块中，基于聚类结果和较低站收入和实用程序的较低站进行加权数字模型。然后，将跨时间段的图形模型组合以创建图形序列模型。在自行车站定位预测模块中，GGNN模型用于培训图形序列数据并在下一个时期动态预测自行车站。在自行车站布局推荐模块中，预测的自行车站根据政府城市管理计划进行了微调，这确保了推荐的站布局有利于城市管理，供应商收入和用户方便。实际DL-PBS网络的实验验证了所提出的BSDP系统的有效性，准确性和可行性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号