Comparison of Machine Learning Approaches in the Prediction of Terrorist Attacks
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/8830728/8844868/08844904.pdf?arnumber=8844904
Cited by 9 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. Systematic Literature Review and Assessment for Cyber Terrorism Communication and Recruitment Activities;Studies in Big Data;2024
2. Predicting the Success of Global Terrorist Attacks Based on Machine Learning;2023 9th Annual International Conference on Network and Information Systems for Computers (ICNISC);2023-10-27
3. AI-Driven Counter-Terrorism: Enhancing Global Security Through Advanced Predictive Analytics;IEEE Access;2023
4. Predicting the Nature of Terrorist Attacks in Nigeria Using Bayesian Neural Network Model;STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health;2023
5. Using Deep Learning Model to Predict Terms Use by Terrorist to Pre-Plan an Attack on A Real-Time Twitter Tweets from Rapid Miner;2022 10th International Conference on Cyber and IT Service Management (CITSM);2022-09-20
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