基于K-means算法的外交机构恐怖主义风险评估

Terrorism Risk Assessment of Diplomatic Agencies Based on K-means Clustering Analysis

[目的/意义]使用K-means聚类分析方法,对外交机构遭受的恐怖主义袭击进行定量、客观的评估。[方法/过程]构造K-means聚类方法风险评估模型,对1970—2018年外交机构遭遇恐怖袭击事件进行分析,客观地计算出几类袭击方式、袭击目标和不同国家的风险,其中重点分析了该外交机构政治隶属和该外交机构地理位置所在国家的恐怖主义风险评估。[结果/结论]K-means算法能减少主观性和人为误差。根据足够规模的数据库,对不同风险等级进行分类,便于直观分析不同风险等级的国家,得到切实可行的反恐对策。

[Purpose/significance]The paper utilizes K-means clustering analysis to make a quantitative and objective assessment of terrorist attacks on diplomatic agencies.[Method/process]The paper constructs K-means clustering method risk assessment model to analyze the terrorist attacks on diplomatic missions from 1970 to 2018,and objectively calculates several types of attack methods,attack targets and different countries risks.Especially,the paper focuses on the terrorism risk assessment analysis of the diplomatic agency’s political affiliation and the geographical location country of the diplomatic agency.[Result/conclusion]K-means algorithm can reduce subjectivity and human error.According to the database of sufficient scale,the classification of different risk levels is convenient for intuitive analysis of countries with different risk levels,and practical counter-terrorism countermeasures can be obtained.