An XGBoost-based casualty prediction method for terrorist attacks
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ORIGINAL ARTICLE
An XGBoost‑based casualty prediction method for terrorist attacks Yi Feng1 · Dujuan Wang1,2 · Yunqiang Yin3 · Zhiwu Li4,5 · Zhineng Hu1 Received: 13 May 2020 / Accepted: 19 June 2020 © The Author(s) 2020
Abstract Terrorist attacks have been becoming one of the severe threats to national public security and world peace. Ascertaining whether the behaviors of terrorist attacks will threaten the lives of innocent people is vital in dealing with terrorist attacks, which has a profound impact on the resource optimization configuration. For this purpose, we propose an XGBoost-based casualty prediction algorithm, namely RP-GA-XGBoost, to predict whether terrorist attacks will cause the casualties of innocent civilians. In the proposed RP-GA-XGBoost algorithm, a novel method that incorporates random forest (RF) and principal component analysis (PCA) is devised for selecting features, and a genetic algorithm is used to tune the hyperparameters of XGBoost. The proposed method is evaluated on the public dataset (Global Terrorism Database, GTD) and the terrorist attack dataset in China. Experimental results demonstrate that the proposed algorithm achieves area under curve (AUC) of 87.00%, and accuracy of 86.33% for the public dataset, and sensitivity of 94.00%, AUC of 94.90% for the terrorist attack dataset in China, which proves the superiority and higher generalization ability of the proposed algorithm. Our study, to the best of our knowledge, is the first to apply machine learning in the management of terrorist attacks, which can provide early warning and decision support information for terrorist attack management. Keywords Terrorist attack · Prediction · Extreme gradient boosting · Feature selection · Area under curve
Introduction Global Terrorism Database defines terrorist attacks as nonstate actors that threaten or actually use illegal force and violence to achieve political, economic, religious or social goals through fear, coercion or intimidation (https://www. start.umd.edu/gtd). All terrorist incidents contain three attributes: (i) the incident must be intentional; (ii) the incident must cause a degree of violence or a direct threat of * Yunqiang Yin [email protected] 1
Business School, Sichuan University, Chengdu 610064, China
2
Institute of Economy and Enterprise Development, Sichuan University, Chengdu 610064, China
3
School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, China
4
School of Electro‑Mechanical Engineering, Xidian University, Xi’an 710071, China
5
Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau SAR
violence; and (iii) the perpetrator of the incident must be sub-national actors (https://www.start.umd.edu/gtd). Many researches emphasize that the purpose of terrorist attacks lies not in the violent act itself, but in furthering specific political, religious and other goal [4, 21]. The occurrence of an incident will not only bring death and injury to innocent p
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