期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2021
卷号：9
期号：7
页码：8483-8490
DOI：10.15680/IJIRCCE.2021.0907110
语种：English
出版社：S&S Publications
摘要：The goal of this research is to use machine learning to forecast the area and nation of a terrorist strike. The research was conducted using the Global Terrorism Database (GTD), an open database that contains a record of terrorist actions from 1970 to 2017. To improve accuracy, four machine learning methods were applied to a subset of characteristics from the dataset. The findings show that if specific characteristics are available, machine learning algorithms may be trained to anticipate the area and nation of a terrorist strike. The work may be utilized to improve global security against terrorist strikes, according to the theory. This research develops an integrated machine learning method for worldwide terrorist activity categorization and analysis. Machine learning-based data mining may be used to forecast terrorist attack occurrences, allowing specialists to acquire a better understanding of what terrorists are thinking in order to strengthen defences against these coordinated attacks.
