中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Spatial Distribution Assessment of Terrorist Attack Types Based on I-MLKNN Model

文献类型:期刊论文

作者Zhao, Ruifang2; Xie, Xiaolan3; Zhang, Xun2,3; Jin, Min1; Hao, Mengmeng3
刊名ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
出版日期2021-08-01
卷号10期号:8页码:22
关键词assessment terrorist attack types I-MLKNN multi-source factors
DOI10.3390/ijgi10080547
通讯作者Zhang, Xun(zhangxun@btbu.edu.cn)
英文摘要Terrorist attacks are harmful to lives and property and seriously affect the stability of the international community and economic development. Exploring the regularity of terrorist attacks and building a model for assessing the risk of terrorist attacks (a kind of public safety risk, and it means the possibility of a terrorist attack) are of great significance to the security and stability of the international community and to global anti-terrorism. We propose a fusion of Inverse Distance Weighting (IDW) and a Multi-label k-Nearest Neighbor (I-MLKNN)-based assessment model for terrorist attacks, which is in a grid-scale and considers 17 factors of socio-economic and natural environments, and applied the I-MLKNN assessment model to assess the risk of terrorist attacks in Southeast Asia. The results show the I-MLKNN multi-label classification algorithm is proven to be an ideal tool for the assessment of the spatial distribution of terrorist attacks, and it can assess the risk of different types of terrorist attacks, thus revealing the law of distribution of different types of terrorist attacks. The terrorist attack risk assessment results indicate that Armed Attacks, Bombing/Explosions and Facility/Infrastructure Attacks in Southeast Asia are high-risk terrorist attack events, and the southernmost part of Thailand and the Philippines are high-risk terrorist attack areas for terrorism. We do not only provide a reference for incorporating spatial features in multi-label classification algorithms, but also provide a theoretical basis for decision-makers involved in terrorist attacks, which is meaningful to the implementation of the international counter-terrorism strategy.
WOS关键词CONFLICT ; RISK ; DIMENSIONALITY ; REDUCTION ; ALGORITHM ; PATTERNS ; THAILAND ; DISTANCE ; TIME
资助项目National Natural Science Foundation of China[42001238] ; Support Project of High-level Teachers in Beijing Municipal Universities in the Period of 13th Five-year Plan[CITTCD201904037] ; R&D Program of Beijing Municipal Education Commission[KM202010011012] ; Postgraduate Research Capacity Improvement Program from Beijing Technology and Business University in 2021
WOS研究方向Computer Science ; Physical Geography ; Remote Sensing
语种英语
WOS记录号WOS:000689301900001
出版者MDPI
资助机构National Natural Science Foundation of China ; Support Project of High-level Teachers in Beijing Municipal Universities in the Period of 13th Five-year Plan ; R&D Program of Beijing Municipal Education Commission ; Postgraduate Research Capacity Improvement Program from Beijing Technology and Business University in 2021
源URL[http://ir.igsnrr.ac.cn/handle/311030/165301]  
专题中国科学院地理科学与资源研究所
通讯作者Zhang, Xun
作者单位1.State Grid Informat & Telecommun Grp Co Ltd, Beijing 102211, Peoples R China
2.Beijing Technol & Business Univ, Beijing Key Lab Big Data Technol Food Safety, Beijing 100048, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Resources Utilizat & Environm Remediat, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714
Zhao, Ruifang,Xie, Xiaolan,Zhang, Xun,et al. Spatial Distribution Assessment of Terrorist Attack Types Based on I-MLKNN Model[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2021,10(8):22.
APA Zhao, Ruifang,Xie, Xiaolan,Zhang, Xun,Jin, Min,&Hao, Mengmeng.(2021).Spatial Distribution Assessment of Terrorist Attack Types Based on I-MLKNN Model.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,10(8),22.
MLA Zhao, Ruifang,et al."Spatial Distribution Assessment of Terrorist Attack Types Based on I-MLKNN Model".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 10.8(2021):22.

入库方式: OAI收割

来源:地理科学与资源研究所

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