Intelligent bridge management via big data knowledge engineering

被引:36
|
作者
Yang, Jianxi [1 ]
Xiang, Fangyue [1 ]
Li, Ren [1 ]
Zhang, Luyi [1 ]
Yang, Xiaoxia [1 ]
Jiang, Shixin [1 ]
Zhang, Hongyi [1 ]
Wang, Di [1 ]
Liu, Xinlong [1 ]
机构
[1] Chongqing Jiaotong Univ, Sch Informat Sci & Engn, Chongqing 400074, Peoples R China
基金
中国国家自然科学基金;
关键词
Intelligent bridge management; Artificial intelligence; Big data knowledge engineering; Knowledge graph; Framework; STRUCTURAL DAMAGE DETECTION; CONVOLUTIONAL NEURAL-NETWORK; INTEGRATION; RECOGNITION; EXTRACTION; ONTOLOGIES; FRAMEWORK; GRAPH; PERFORMANCE; CHALLENGES;
D O I
10.1016/j.autcon.2021.104118
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Fully combining the emerging intelligent technologies, such as big data and artificial intelligence, to realize the effective data fusion of bridge management with multi-source, autonomous, massive, heterogeneous features, and to further improve the capability of domain knowledge sharing and services have become the urgent demand and future development trend in the field of bridge engineering. This paper summarizes the business background and big data characteristics of bridge management, and represents a brief review of related work. According to the big data knowledge engineering paradigm, this paper proposes a novel BigKE-based intelligent bridge management and maintenance framework consisting of the layers of data-sources, storage and computing, knowledge representation, knowledge computing, and knowledge services. The corresponding main research contents involved in each layer are discussed as well. Finally, we point out some possible application scenarios and main challenges of the proposed framework, which elaborate on areas for future research.
引用
收藏
页数:14
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