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

<p>In this paper, there is no unified grading standard for the harm of terrorist attacks. A classification model of terrorist incidents based on machine learning is proposed. First, the data related to the hazard in the Global Terrorism Database (GTD) is extracted and preprocessed. Secondly, the data is extracted by principal component analysis, and all events are aggregated into 5 by K-means clustering. Again, the entropy method is used to calculate the weighting coefficient of each indicator, and the comprehensive score of the hazard of each type of terrorist attack is calculated. Finally, the scores are divided into 1-5 levels of hazard grading models in order of high to low. The results show that the hazard grading model can scientifically and objectively quantify terrorist attacks.</p>
</abstract>

In this paper, there is no unified grading standard for the harm of terrorist attacks. A classification model of terrorist incidents based on machine learning is proposed. First, the data related to the hazard in the Global Terrorism Database (GTD) is extracted and preprocessed. Secondly, the data is extracted by principal component analysis, and all events are aggregated into 5 by K-means clustering. Again, the entropy method is used to calculate the weighting coefficient of each indicator, and the comprehensive score of the hazard of each type of terrorist attack is calculated. Finally, the scores are divided into 1-5 levels of hazard grading models in order of high to low. The results show that the hazard grading model can scientifically and objectively quantify terrorist attacks.

Hazard Grading Model of Terrorist Attack Based on Machine Learning

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Hazard Grading Model of Terrorist Attack Based on Machine Learning"}

In this paper, there is no unified grading standard for the harm of terrorist attacks. A classification model of terrorist incidents based on machine learning...

Hazard Grading Model of Terrorist Attack Based on Machine Learning

Pubblicato online: 08 ott 2019

Pagine: 81 - 85

DOI: https://doi.org/10.21307/ijanmc-2019-051

Parole chiave
Terrorist Attacks, Hazard, Hierarchical Model, Principal Component Analysis, K-Means Clustering, Entropy Method

© 2019 Yu Jun et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Hazard Grading Model of Terrorist Attack Based on Machine Learning

Pubblicato online: 08 ott 2019

Pagine: 81 - 85

DOI: https://doi.org/10.21307/ijanmc-2019-051

Parole chiaveTerrorist Attacks, Hazard, Hierarchical Model, Principal Component Analysis, K-Means Clustering, Entropy Method

© 2019 Yu Jun et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Parole chiave
Terrorist Attacks, Hazard, Hierarchical Model, Principal Component Analysis, K-Means Clustering, Entropy Method