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基于RailBERT的列控车载ATP测试案例事件抽取方法研究

程烨 李开成 魏国栋

北京交通大学学报2024,Vol.48Issue(5):10-20,11.
北京交通大学学报2024,Vol.48Issue(5):10-20,11.DOI:10.11860/j.issn.1673-0291.20230170

基于RailBERT的列控车载ATP测试案例事件抽取方法研究

Research on RailBERT-based event extraction method for test cases of train control system on-board ATP

程烨 1李开成 1魏国栋1

作者信息

  • 1. 北京交通大学 自动化与智能学院,北京 100044
  • 折叠

摘要

Abstract

In the laboratory testing of Automatic Train Protection(ATP)onboard equipment,the large volume and high complexity of test cases,combined with numerous specialized terms in the train con-trol domain,pose significant challenges for existing methods and models.These approaches often lack domain-specific knowledge,making it difficult to accurately interpret contextual information and auto-matically generate detailed structured representations.To address these challenges,this paper pro-poses an event extraction method for test cases based on the Rail Bidirectional Encoder Representa-tions from Transformers(RailBERT)model.First,a corpus of specialized terms in the train control domain is expanded and constructed using a neologism mining algorithm.A RailBERT model tailored to the train control system domain is then pre-trained with a Railway Whole Word Masking(RWWM)task to improve its understanding of domain-specific contexts.Then,an event extraction approach is developed to automatically extract the expected outcomes of onboard ATP test cases.The predefined event types and event theory elements are used to achieve comprehensive parsing and characterization of the expected results.Finally,the RailBERT is integrated with Bidirectional Long Short-Term Memory(BiLSTM)and Conditional Random Field(CRF)to enhance its ability to capture dependen-cies between sequence information and labels,thereby enabling more effective event extraction from test cases.The experimental results show that the proposed model achieves an F1 score of 90.3%on the test case event extraction dataset.This model accurately extracts predefined events from test cases and generates structured representations of the expected outcomes,providing a foundation for the implementation of automated testing.

关键词

车载设备/测试案例/自然语言处理/事件抽取/预训练模型

Key words

onboard equipment/test case/natural language processing/event extraction/pre-trained model

分类

交通工程

引用本文复制引用

程烨,李开成,魏国栋..基于RailBERT的列控车载ATP测试案例事件抽取方法研究[J].北京交通大学学报,2024,48(5):10-20,11.

基金项目

国家自然科学基金(52372310) (52372310)

中央高校基本科研业务费专项资金(2024JBGP005) (2024JBGP005)

中国国家铁路集团有限公司科技研究开发计划(N2023G068(JB)) (N2023G068(JB)

四川省科技计划(2022-ZY00-00004-GX) National Natural Science Foundation of China(52372310) (2022-ZY00-00004-GX)

Fundamental Research Funds for the Central Universities(2024JBGP005) (2024JBGP005)

China State Railway Group Co.,Ltd.Science and Technology Research and Development Program Project(N2023G068(JB)) (N2023G068(JB)

Sichuan Science and Technology Program(2022-ZY00-00004-GX) (2022-ZY00-00004-GX)

北京交通大学学报

OA北大核心CSTPCD

1673-0291

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