Knowledge Commons of Institute of Automation,CAS
Fault Information Recognition for On-board Equipment of High-speed Railway Based on Multi-neural Network Collaboration | |
Lu-Jie Zhou1; Jian-Wu Dang1,2; Zhen-Hai Zhang1 | |
发表期刊 | International Journal of Automation and Computing
![]() |
ISSN | 1476-8186 |
2021 | |
卷号 | 18期号:6页码:935-946 |
摘要 | It is of great significance to guarantee the efficient statistics of high-speed railway on-board equipment fault information, which also improves the efficiency of fault analysis. Considering this background, this paper presents an empirical exploration of named entity recognition (NER) of on-board equipment fault information. Based on the historical fault records of on-board equipment, a fault information recognition model based on multi-neural network collaboration is proposed. First, considering Chinese recorded data characteristics, a method of constructing semantic features and additional features based on character granularity is proposed. Then, the two feature representations are concatenated and passed into the gated convolutional layer to extract the dependencies from multiple different subspaces and adjacent characters in parallel. Next, the local features are transmitted to the bidirectional long short-term memory (BiLSTM) to learn long-term dependency information. On top of BiLSTM, the sequential conditional random field (CRF) is used to jointly decode the optimized tag sequence of the whole sentence. The model is tested and compared with other representative baseline models. The results show that the proposed model not only considers the language characteristics of on-board fault records, but also has obvious advantages on the performance of fault information recognition. |
关键词 | Train control system Chinese named entity recognition (NER) character feature gating mechanism bidirectional long short-term memory (BiLSTM) |
DOI | 10.1007/s11633-021-1298-8 |
七大方向——子方向分类 | 其他 |
国重实验室规划方向分类 | 其他 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/46100 |
专题 | 学术期刊_Machine Intelligence Research |
作者单位 | 1.School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China 2.Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphic & Image Processing, Lanzhou 730070, China |
推荐引用方式 GB/T 7714 | Lu-Jie Zhou,Jian-Wu Dang,Zhen-Hai Zhang. Fault Information Recognition for On-board Equipment of High-speed Railway Based on Multi-neural Network Collaboration[J]. International Journal of Automation and Computing,2021,18(6):935-946. |
APA | Lu-Jie Zhou,Jian-Wu Dang,&Zhen-Hai Zhang.(2021).Fault Information Recognition for On-board Equipment of High-speed Railway Based on Multi-neural Network Collaboration.International Journal of Automation and Computing,18(6),935-946. |
MLA | Lu-Jie Zhou,et al."Fault Information Recognition for On-board Equipment of High-speed Railway Based on Multi-neural Network Collaboration".International Journal of Automation and Computing 18.6(2021):935-946. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
IJAC-2020-09-268.pdf(1263KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论