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

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning techniques to predict terrorist attacksby Laura Mostert ... [et al.].
其他題名:	exemplified by Jama'at Nasr al-Islam wal Muslimin /
其他作者:	Mostert, Laura.
出版者:	Cham :Springer Nature Switzerland :2025.
面頁冊數:	xv, 132 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	TerrorismData processing.
電子資源:	https://doi.org/10.1007/978-3-031-93174-1
ISBN:	9783031931741$q(electronic bk.)

Machine learning techniques to predict terrorist attacksexemplified 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$q(electronic bk.)

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

283807
Terrorism
--Data processing.

LC Class. No.: HV6431

Dewey Class. No.: 363.3250285631

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