首页    期刊浏览 2024年10月03日 星期四
登录注册

文章基本信息

  • 标题:Grid text classification method based on DNN neural network
  • 本地全文:下载
  • 作者:Jutao Huang ; Jiesheng Zheng ; Shang Gao
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2020
  • 卷号:309
  • 页码:1-6
  • DOI:10.1051/matecconf/202030903016
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:With the rapid development of network technology, the electric power Internet of Things needs to face a large number of electronic texts and a large number of distributed data access and analysis requirements. If the system wants to complete accurate and efficient data analysis and build an existing data and service standard system covering the entire chain of energy and power business on the existing basis, it must implement massive electronic text retrieval, information extraction and classification in the power grid system. In order to achieve this purpose, a DNN neural network classification model is constructed to classify the text information of the power grid, and the effectiveness of the method is verified by experiments based on data from the substation information system.
  • 关键词:Keywords:enNatural language processingText classificationDNN network
国家哲学社会科学文献中心版权所有