Predicting the success of suicide terrorist attacks using different machine learning algorithms

• Main Authors: Hossain, Md Junayed, Abdullah, Sheikh Md, Barkatullah, Mohammad, Miahh, Md Saef Ulla, Sarwar, Talha, Monir, Md Fahad
• Format: Conference or Workshop Item
• Language: English; English
• Published: Institute of Electrical and Electronics Engineers Inc. 2022
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/39083/1/Predicting%20the%20success%20of%20suicide%20terrorist%20attacks%20using%20different%20machine.pdf; http://umpir.ump.edu.my/id/eprint/39083/2/Predicting%20the%20success%20of%20suicide%20terrorist%20attacks%20using%20different%20machine%20learning%20algorithms_ABS.pdf; http://umpir.ump.edu.my/id/eprint/39083/; https://doi.org/10.1109/ICCIT57492.2022.10055100

Extremism has become one of the major threats throughout the world over the past few decades. In the last two decades, there has been a sharp increase in extremism and terrorist attacks. Nowadays, terrorism concerns all nations in terms of national security and is considered one of the most priority...