一种新的方法来计算基于粗略的集合理论的加权二图的单源最短路径
Mingfeng Hua1, Taihua Xu1,2, Xibei Yang1
1School of Computer, Jiangsu University of Science and Technology, Zhenjiang 212100, China.
Mathematical biosciences and engineering : MBE
|March 8, 2024
概括
本研究引入了一种新的Rough Sets Theory (RST) 方法,用于在加权二图中计算单源最短路径 (SSSP). W3SP@R算法提高了图形路径查找的效率和精度.
科学领域:
- 图形理论 图形理论
- 粗集理论 (RST) 是一个理论.
- 算法开发 算法开发
背景情况:
- 单源最短路径 (SSSPs) 在加权二位图中是至关重要的.
- 粗集理论 (RST) 为图形问题分析提供了新的方法.
- 现有的RST方法已经在子图发现方面取得了成功.
研究的目的:
- 开发一种基于RST的新方法,用于在加权双图中计算SSSP.
- 通过使用RST.ST.提高SSSP计算的效率和精度.
- 建立用于将RST应用于SSSP问题的理论基础.
主要方法:
- 通过RST的透视来探讨SSSP的问题,以获得理论支持.
- 设计一个启发式搜索策略,利用边缘权重作为优化信息.
- 开发了W3SP@R算法,一种基于RST的SSSP计算方法.
主要成果:
- 在W3SP@R算法精确地计算SSSP在加权二图.
- 实验结果表明,与现有方法相比,具有竞争力的效率.
- 启发式搜索策略有效地优化了SSSP的发现.
结论:
- 通过利用RST和启发式搜索,W3SP@R算法为SSSP提供了一个有效的解决方案.
- 这项工作验证了RST在解决复杂的图形理论问题的应用性.
- 拟议的方法提供了一种精确而有效的方法,用于加权的二位图路径查找.
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