Research on Intelligent Statistical Analysis of Wargaming Data Based on NL2SQL

doi:10.16182/j.issn1004731x.joss.22-0559

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 in-depth 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 datais 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 time-sensitive 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%.

Key words: wargaming, NL2SQL(natural language to struct query language), dataset, time processing, statistical query

CLC Number:

TP31

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.

Figures/Tables 8

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参数	值	参数	值
BERT-wmm	默认参数	损失函数	交叉熵
LSTM隐藏层	400	激活函数	ReLU
注意力头	8	Drop_out	0.3
学习率	5×10^-4	Epoch	10
优化器	Adam	Batch Size	64

模型	DuSQL	BqSQL
Bridge	43.1	15.5
本模型	45.6	18.1

方式	验证集	测试集
BqSQL	66.13	62.9
公开数据集+BqSQL	81.20	75.7

模型	测试集
基础模型	38.3
基础模型+时间规范	51.6
基础模型+值匹配	65.2

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