斯洛文尼亚自行车道的Neo4j图形数据集
1Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, Maribor SI-2000, Slovenia.
Data in brief
|June 29, 2023
概括
本研究介绍了一个基于图形的数据集,用于优化骑自行车训练路线. 该数据集考虑了不仅仅是距离和时间之外的因素,从而实现了个性化的培训计划.
科学领域:
- 计算机科学 计算机科学
- 运动科学 运动科学 运动科学
- 图形理论 图形理论
背景情况:
- 现实世界的导航可以作为图形建模,节点作为交叉点,边缘作为道路.
- 为骑自行车训练优化路线不同于找到最短或最快的路径,需要考虑训练特定的参数.
研究的目的:
- 呈现斯洛文尼亚自行车路线的全面的Neo4j图形数据集.
- 促进开发先进的自行车训练生成算法.
主要方法:
- 使用Neo4j.构建了一个图形数据集.
- 数据集包括152,659个节点 (十字路口) 和410,922个边缘 (道路).
主要成果:
- 现在可以获得斯洛文尼亚自行车路线的详细基于图形的数据集.
- 该数据集可以将距离,上升,下降和道路类型纳入路线优化中.
结论:
- 这一数据集对于开发智能自行车训练算法的研究人员来说是一个宝贵的资源.
- 这项工作支持创建个性化自行车训练计划,根据运动员的个性参数量身定制.
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