智能科学与技术学报2024，Vol.6Issue(2)：201-209,9.DOI:10.11959/j.issn.2096-6652.202419
基于模糊自然语言处理的铁路CTC接口文本智能测试方法
Intelligent testing method for railway CTC interface data based on fuzzy natural language processing
摘要
Abstract
Fuzzy natural language processing applies fuzzy theoretical knowledge to the task of natural language process-ing(NLP).With the continuous development of large language model and artificial intelligence,research on text data con-tinues to deepen.As a large and complex system,the interface data between various subsystems and server software are stored and transmitted in log text format.Due to its large number of texts and miscellaneous text types,a fuzzy NLP method was proposed to solve the problem of manual testing the interface data of centralized traffic control(CTC)sys-tem.The fuzzy C-means(FCM)clustering algorithm divided the log text into different label categories,which was used as the label input for named entity recognition in NLP tasks,and BERT was introduced on the traditional BiLSTM-CRF model for text encoding,which understood the relationship between texts more accurately and improved the accuracy of text recognition.An intelligent verification tool for log-text interface testing of railway CTC system was presented based on an improved training model,which enhanced the current manual testing process of CTC system,assisted testing staff in verifying the interface testing,and increased the level of intelligence and automation in testing work.关键词
自然语言处理/模糊文本聚类/铁路调度集中控制系统/命名实体识别/智能测试Key words
natural language processing/fuzzy text clustering/railway centralized traffic control system/named entity recognition/intelligent testing分类
交通工程引用本文复制引用
角远韬,李润梅,王剑..基于模糊自然语言处理的铁路CTC接口文本智能测试方法[J].智能科学与技术学报,2024,6(2):201-209,9.基金项目
国家重点研发计划(No.2022YFB4300500) （No.2022YFB4300500）
中国国家铁路集团有限公司科技研究开发计划(No.L2022X002) National Key R&D Program of China(No.2022YFB4300500),Technological R&D Program of China state Rail-way Group Co.,Ltd.China Railway Project(No.L2022X002) （No.L2022X002）
