Research on Anti-terrorism Intelligence Mining Method Based on Attention Neural Networks

被引：1

作者：

Bai, Caitong ^{[1
,4
]}

Li, Ai ^{[1
,4
]}

Gao, Zhiqiang ^{[1
,3
,4
]}

Cui, Xiaolong ^{[2
,4
]}

机构：

[1] Engn Univ PAP, Grad Grp, Xian 710086, Peoples R China

[2] Engn Univ PAP, Lu Mu Campus, Urumqi 830049, Xinjiang, Peoples R China

[3] Engn Univ PAP, Coll Informat Engn, Xian 710086, Peoples R China

[4] Armed Police Engn Univ, Antiterrorism Command Informat Engn Res Team, Xian, Peoples R China

来源：

PROCEEDINGS OF 2020 IEEE 2ND INTERNATIONAL CONFERENCE ON CIVIL AVIATION SAFETY AND INFORMATION TECHNOLOGY (ICCASIT) | 2020年

基金：

中国国家自然科学基金;

关键词：

Global anti-terrorism Data Set; Open Source Intelligence Mining Neural Network; Attention Mechanism;

D O I：

10.1109/ICCASIT50869.2020.9368596

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

In order to improve the intelligence and prediction accuracy of anti-terrorism intelligence mining, this paper applies a medium of attraction neural network based on attention mechanism and investors will own a Complete set of open Source Intelligence Data Mining and takes the analysis of casualties and terrorist organizations as examples and a prediction model of casualties and potential about organizations is constructed. It has had been experimentally verified that its prediction ability is significantly improved compared to support vector machine algorithm, logistic regression algorithm, multi-layer perceptron and attention neural network.

引用

页码：458 / 464

页数：7

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