The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Dec. 12, 2023
Filed:
Oct. 14, 2022
Hohai University, Nanjing, CN;
Huaneng Lancang River Hydropower Inc., Kunming, CN;
Huaneng Group Tech Innovation Center Co., Ltd., Beijing, CN;
Yingchi Mao, Nanjing, CN;
Wei Sun, Kunming, CN;
Haibin Xiao, Kunming, CN;
Fudong Chi, Kunming, CN;
Hao Chen, Kunming, CN;
Weiyong Zhan, Kunming, CN;
Fugang Zhao, Kunming, CN;
Han Fang, Kunming, CN;
Xiaofeng Zhou, Nanjing, CN;
Chunrui Zhang, Kunming, CN;
Bin Tan, Kunming, CN;
Wenming Xie, Kunming, CN;
Bingbing Nie, Kunming, CN;
Zhixiang Chen, Kunming, CN;
Chunrui Yang, Kunming, CN;
HOHAI UNIVERSITY, Nanjing, CN;
HUANENG LANCANG RIVER HYDROPOWER INC., Kunming, CN;
HUANENG GROUP TECH INNOVATION CENTER CO., LTD., Beijing, CN;
Abstract
A method for extracting a dam emergency event based on a dual attention mechanism is provided. The method includes: performing data preprocessing, building a dependency graph, building a dual attention network, and filling a document-level argument. The performing data preprocessing includes labeling a dam emergency corpus and encoding sentences. Building a dependency graph includes assisting a model to mine a syntactic relation based on a dependency. Building a dual attention network includes weighing and fusing an attention network based on a graph transformer network (GTN) and capturing key semantic information in the sentence. Filling a document-level argument includes filling a document-level argument by detecting a key sentence and ordering a semantic similarity. The method introduces a dependency and overcomes the long-range dependency problem based on the dual attention mechanism, thus achieving high identification accuracy and reducing a lot of labor costs.