A two-step machine learning method for casualty prediction under emergencies-Reference-Cited by-同舟云学术

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A two-step machine learning method for casualty prediction under emergencies

Published:2022-09 Issue:3 Volume:3 Page:243-251
ISSN:2666-4496
Container-title:Journal of Safety Science and Resilience
language:en
Short-container-title:Journal of Safety Science and Resilience

Author:

Hu Xiaofeng,Hu Jinming,Hou Miaomiao

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Safety Research,Safety, Risk, Reliability and Quality,Statistics, Probability and Uncertainty,Management Science and Operations Research,Computer Science Applications

Reference41 articles.

1. An XGBoost-based casualty prediction method for terrorist attacks;Feng;Complex Intell. Syst.,2020

2. Predictive modeling of terrorist attacks using machine learning;JSPM;Int. J. Pure Appl. Math.,2018

3. A three-stage evacuation decision-making and behavior model for the onset of an attack;Li;Transp. Res. Part C Emerg. Technol.,2017

4. An analysis of the crucial indicators impacting the risk of terrorist attacks: a predictive perspective;Luo;Saf. Sci.,2021

5. Big data-based prediction of terrorist attacks;Meng;Comput. Electr. Eng.,2019

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fostering Global Stability: Machine Learning for Anticipating Terrorism;2023 International Conference on Integrated Intelligence and Communication Systems (ICIICS);2023-11-24

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