计算机工程与应用 ›› 2025, Vol. 61 ›› Issue (5): 43-54.DOI: 10.3778/j.issn.1002-8331.2404-0043
张建伟,陈旭,王叔洋,景永俊,宋吉飞
出版日期:
2025-03-01
发布日期:
2025-03-01
ZHANG Jianwei, CHEN Xu, WANG Shuyang, JING Yongjun, SONG Jifei
Online:
2025-03-01
Published:
2025-03-01
摘要: 随着物联网在各个领域物理设备的发展,产生的大量数据给当前数据处理方法带来了挑战。深度学习模型具备处理大规模和高维度数据的能力,已逐渐应用于物联网不同领域。时空图神经网络作为一种处理图结构数据的深度学习模型,能够对物联网中的拓扑结构和时间信息进行建模,并在物联网预测任务中展现出优秀性能。介绍了物联网中的时间相关性和空间相关性,以及不同时空网络架构的构建方法,并基于空间相关性的不同,将时空图神经网络分为时空图卷积网络和时空图注意力网络。进一步分析了时空图卷积网络和时空图注意力网络在物联网中的应用,主要包括交通、环境和能源领域。最后,探讨了时空图神经网络在物联网应用中面临的挑战和未来的研究方向。
张建伟, 陈旭, 王叔洋, 景永俊, 宋吉飞. 时空图神经网络在物联网中的应用综述[J]. 计算机工程与应用, 2025, 61(5): 43-54.
ZHANG Jianwei, CHEN Xu, WANG Shuyang, JING Yongjun, SONG Jifei. Review of Application of Spatiotemporal Graph Neural Networks in Internet of Things[J]. Computer Engineering and Applications, 2025, 61(5): 43-54.
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