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Machine Learning Techniques to Predict Terrorist Attacks
Exemplified by Jama'at Nasr al-Islam wal Muslimin
- Serie -
- Computer Science (R0)
2025
EN
Accessible
One of the most influential actors in spreading Islamist violence across the Sahel is Jama’at Nasr Al Islam Wal Muslimin (JNIM).This book provides the first systematic quantitative analysis of JNIM’s behavior by analyzing a 12-year database of JNIM’s attacks and the environment surrounding JNIM. This book leverages AI/ML predictive models to accurately predict almost 40 types of attacks using over 80 independent variables.This book describes a set of temporal probabilistic rules th...
$920.00 MXN
2020
EN
This is the first study of Boko Haram that brings advanced data-driven, machine learning models to both learn models capable of predicting a wide range of attacks carried out by Boko Haram, as well as develop data-driven policies to shape Boko Haram’s behavior and reduce attacks by them. This book also identifies conditions that predict sexual violence, suicide bombings and attempted bombings, abduction, arson, looting, and targeting of government officials and security installations....
$2,391.00 MXN

