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Autor(en): 
  • V.S. Subrahmanian
  • Roy Lindelauf
  • Chiara Pulice
  • Laura Mostert
  • Marnix Provoost
  • Priyanka Amin
  • Machine Learning Techniques to Predict Terrorist Attacks: Exemplified by Jama'at Nasr al-Islam wal Muslimin 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Juli 2025  
    Genre:  EDV / Informatik 
     
    Africa / Artificial Intelligence / forecasting, counterterrorism / international conflict / Krieg und Verteidigung / Künstliche Intelligenz / machine learning / Military and Defence Studies
    ISBN:  9783031931734 
    EAN-Code: 
    9783031931734 
    Verlag:  Springer International Publishing 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Seiten:  132 
    Illustration:  XV, 132 p. 30 illus., 29 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    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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