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This is an outdated version published on 2026-05-26. Read the most recent version.

An Efficient Methodology to Predict the Terrorist Threat Using Data Fusion Approach for Warning Indications

Authors
  • Saurabh Singh

    Author
  • Akhilesh Tiwari

    Author
Keywords:
Modeling and prediction, Data mining, Data models, Graphics processors
Abstract

Terrorist network analysis is important for predicting terror attacks and for obtaining significant data from unauthenticated data available. Graphical analysis is the most instructive tool for interpreting complex terror networks. In the proposed study, the data set from the 26/11 Mumbai attack terrorist was considered for analyzing the terrorist network by employing a data fusion approach. The study also focuses on identifying the key node to predict the terror threat accurately. From the measurement analysis, it was found that Wassi was predominant in leading the attack and was a prominent controlling agent. The data was in alignment with the report obtained from the government

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Published
2026-05-26
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How to Cite

An Efficient Methodology to Predict the Terrorist Threat Using Data Fusion Approach for Warning Indications. (2026). Journal of Integrated Engineering Innovation & Applications, 2(1 (March 2026). https://joieia.com/index.php/home/article/view/16

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