Journal of System Simulation
Abstract
Abstract: In the face of massive wargaming data, the traditional interface query method can no longer meet the commander's requirements, i. e., fast, comprehensive, and accurate data querying. Through indepth analysis of the characteristics of wargaming data and the defects of the mainstream natural language to struct query language (NL2SQL) model, a set of solutions for the intelligent statistical query of wargaming data is presented. Due to the lack of datasets, a wargaming dataset construction scheme based on human-machine assistance and dynamic iteration is provided. In order to solve the timesensitive problem of wargaming querying, time expression recognition and standardization methods based on "rule + deep learning" are proposed. The value extraction and SQL generation architecture of the Bridge model are modified to facilitate the extraction of query value for a large amount of wargaming data. By comprehensively using the above scheme, the query accuracy of wargaming data is significantly enhanced to more than 75%.
Recommended Citation
Yin, Laixiang; Li, Zhiqiang; and Fu, Qiongying
(2023)
"Research on Intelligent Statistical Analysis of Wargaming Data Based on NL2SQL,"
Journal of System Simulation: Vol. 35:
Iss.
9, Article 14.
DOI: 10.16182/j.issn1004731x.joss.22-0559
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol35/iss9/14
First Page
2000
Last Page
2010
CLC
TP31; TP391.9
Recommended Citation
Yin Laixiang, Li Zhiqiang, Fu Qiongying. Research on Intelligent Statistical Analysis of Wargaming Data Based on NL2SQL[J]. Journal of System Simulation, 2023, 35(9): 2000-2010.
DOI
10.16182/j.issn1004731x.joss.22-0559
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons