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Machine learning techniques to predict terrorist attacks = exemplified by Jama'at Nasr al-Islam wal Muslimin /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning techniques to predict terrorist attacks/ by Laura Mostert ... [et al.].
Reminder of title:	exemplified by Jama'at Nasr al-Islam wal Muslimin /
other author:	Mostert, Laura.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xv, 132 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Chapter 1 Introduction -- Chapter 2 Jama'at Nasr al-Islam wal Muslimin (JNIM) -- Chapter 3 Temporal Probabilistic Rules and Policy Computation Algorithms -- Chapter 4 Abduction and Release of Abductees -- Chapter 5 Attacks on and Targeting of Public Sites -- Chapter 6 Targeting of Security Professionals and Security Installations -- Chapter 7 Targeting of Civilians -- Chapter 8 Other types of attacks -- Chapter 9 Reflections & Implications for military decision making.
Contained By:	Springer Nature eBook
Subject:	Terrorism - Data processing. -
Online resource:	https://doi.org/10.1007/978-3-031-93174-1
ISBN:	9783031931741

Machine learning techniques to predict terrorist attacks = exemplified by Jama'at Nasr al-Islam wal Muslimin /
Machine learning techniques to predict terrorist attacksexemplified by Jama'at Nasr al-Islam wal Muslimin /[electronic resource] :by Laura Mostert ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xv, 132 p. :ill. (some col.), digital ;24 cm. - Terrorism, security, and computation,2197-8786. - Terrorism, security, and computation..

Chapter 1 Introduction -- Chapter 2 Jama'at Nasr al-Islam wal Muslimin (JNIM) -- Chapter 3 Temporal Probabilistic Rules and Policy Computation Algorithms -- Chapter 4 Abduction and Release of Abductees -- Chapter 5 Attacks on and Targeting of Public Sites -- Chapter 6 Targeting of Security Professionals and Security Installations -- Chapter 7 Targeting of Civilians -- Chapter 8 Other types of attacks -- Chapter 9 Reflections & Implications for military decision making.

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 that state that when the environment in which the group operates satisfies some conditions, then an attack of a certain type will likely occur in the next N months. This provides a deep, easy to comprehend understanding of the conditions under which JNIM carries various kinds of attacks up to 6 months into the future. This book will serve as an invaluable guide to scholars (computer scientists, political scientists, policy makers). Military officers, intelligence personnel, and government employees, who seek to understand, predict, and eventually mitigate attacks by JNIM and bring peace to the nations of Mali, Burkina Faso, and Niger will want to purchase this book as well.

ISBN: 9783031931741

Standard No.: 10.1007/978-3-031-93174-1doiSubjects--Topical Terms:

907040
Terrorism
--Data processing.

LC Class. No.: HV6431

Dewey Class. No.: 363.3250285631

Machine learning techniques to predict terrorist attacks = exemplified by Jama'at Nasr al-Islam wal Muslimin /
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245 0 0 $a Machine learning techniques to predict terrorist attacks $h [electronic resource] : $b exemplified by Jama'at Nasr al-Islam wal Muslimin / $c by Laura Mostert ... [et al.].
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490 1 $a Terrorism, security, and computation, $x 2197-8786
505 0 $a Chapter 1 Introduction -- Chapter 2 Jama'at Nasr al-Islam wal Muslimin (JNIM) -- Chapter 3 Temporal Probabilistic Rules and Policy Computation Algorithms -- Chapter 4 Abduction and Release of Abductees -- Chapter 5 Attacks on and Targeting of Public Sites -- Chapter 6 Targeting of Security Professionals and Security Installations -- Chapter 7 Targeting of Civilians -- Chapter 8 Other types of attacks -- Chapter 9 Reflections & Implications for military decision making.
520 $a 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 that state that when the environment in which the group operates satisfies some conditions, then an attack of a certain type will likely occur in the next N months. This provides a deep, easy to comprehend understanding of the conditions under which JNIM carries various kinds of attacks up to 6 months into the future. This book will serve as an invaluable guide to scholars (computer scientists, political scientists, policy makers). Military officers, intelligence personnel, and government employees, who seek to understand, predict, and eventually mitigate attacks by JNIM and bring peace to the nations of Mali, Burkina Faso, and Niger will want to purchase this book as well.
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650 0 $a Terrorism $x Prevention $x Data processing. $3 3789236
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650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Military and Defence Studies. $3 2181953
650 2 4 $a Terrorism and Political Violence. $3 2182328
700 1 $a Mostert, Laura. $3 3789235
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830 0 $a Terrorism, security, and computation. $3 2139163
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