<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In counter-terrorism actions, commanders are confronted with difficult and important challenges. Their decision-making processes follow military instructions and must consider the humanitarian aspect of the mission. In this paper, we aim to respond to the question: <italic>What would the casualties be if governmental forces reacted in a given way with given resources?</italic> Within a similar context, decision-support systems are required due to the variety and complexity of modern attacks as well as the enormous quantity of information that must be treated in real time. The majority of mathematical models are not suitable for real-time events. Therefore, we propose an analytical model for a time-dependent prediction of terrorist attacks (ATiPreTA). The output of our model is consistent with casualty data from two important terrorist events known in Tunisia: Bardo and Sousse attacks. The sensitivity and experimental analyses show that the results are significant. Some operational insights are also discussed.</p>
</abstract>

In counter-terrorism actions, commanders are confronted with difficult and important challenges. Their decision-making processes follow military instructions and must consider the humanitarian aspect of the mission. In this paper, we aim to respond to the question: What would the casualties be if governmental forces reacted in a given way with given resources? Within a similar context, decision-support systems are required due to the variety and complexity of modern attacks as well as the enormous quantity of information that must be treated in real time. The majority of mathematical models are not suitable for real-time events. Therefore, we propose an analytical model for a time-dependent prediction of terrorist attacks (ATiPreTA). The output of our model is consistent with casualty data from two important terrorist events known in Tunisia: Bardo and Sousse attacks. The sensitivity and experimental analyses show that the results are significant. Some operational insights are also discussed.

ATiPreTA: AN Analytical Model for Time–Dependent Prediction of Terrorist Attacks

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

In counter-terrorism actions, commanders are confronted with difficult and important challenges. Their decision-making processes follow military instructions...

ATiPreTA: AN Analytical Model for Time–Dependent Prediction of Terrorist Attacks

Online veröffentlicht: 08. Okt. 2022

Seitenbereich: 495 - 510

Eingereicht: 03. Sept. 2021

Akzeptiert: 27. Jan. 2022

DOI: https://doi.org/10.34768/amcs-2022-0036

Schlüsselwörter
terrorist attacks, attack classification, mathematical modeling, dynamic behavior simulation, damage prediction

© 2022 Oussama Kebir et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

ATiPreTA: AN Analytical Model for Time–Dependent Prediction of Terrorist Attacks

Online veröffentlicht: 08. Okt. 2022

Seitenbereich: 495 - 510

Eingereicht: 03. Sept. 2021

Akzeptiert: 27. Jan. 2022

DOI: https://doi.org/10.34768/amcs-2022-0036

Schlüsselwörterterrorist attacks, attack classification, mathematical modeling, dynamic behavior simulation, damage prediction

© 2022 Oussama Kebir et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
terrorist attacks, attack classification, mathematical modeling, dynamic behavior simulation, damage prediction