基于知识图的自然灾害的语义路径引导遥感建议
Xiangyu Zhao1, Chunju Zhang1, Chenchen Luo1
1College of Civil Engineering, Hefei University of Technology, Hefei 230009, China.
Sensors (Basel, Switzerland)
|September 13, 2025
概括
本研究介绍了一种知识图法,用于推用于自然灾害数据采集的遥感传感器. 该方法通过使用语义路径指导来提高任务匹配和建议效率.
科学领域:
- 地理空间科学 地理空间科学
- 数据科学数据科学数据科学
- 灾害管理 灾害管理
背景情况:
- 对于自然灾害的遥感数据采集在任务匹配,语义表示和建议效率方面面临挑战.
- 现有的方法难以将灾难特定需求与可用的遥感资源相匹配的复杂性.
研究的目的:
- 为智能遥感任务传感器在灾难场景中进行匹配提出一种新的语义路径引导推方法.
- 提高选择自然灾害监测适当的遥感资源的效率和准确性.
主要方法:
- 构建面向灾难的遥感知识图,整合灾难类型,任务,传感器和平台等实体.
- 使用Meta-Path2Vec通过路径受约束的随机走路和Skip-Gram来捕捉语义关系来学习节点嵌入.
- 应用同位素相似性和Top-K排名用于任务驱动的传感器建议.
主要成果:
- 拟议的方法在各种灾害场景 (洪水,山体滑坡,野火) 的实验中显示出高精度和强大的稳定性.
- 开发了一个交互式推系统,验证了该方法在现实应用中的实际有效性.
- 该方法成功地解决了复杂任务匹配的挑战,并改善了远程传感数据采集的语义表示.
结论:
- 语义路径指导的推方法为灾难环境中智能遥感数据采集提供了重大进步.
- 这项工作为优化传感器选择和数据匹配以应对灾害提供了理论基础和实际解决方案.
- 开发的知识图框架和嵌入机制增强了对遥感资源的理解和利用,用于灾害管理.
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