Machine Learning based Terrorist Attacks Prediction Algorithm
Yuanyuan Wang · Applied and Computational Engineering · 2023
Terrorist attacks are spreading rapidly all over the world, which has caused heavy casualties and property losses. Therefore, it is very necessary to predict precisely the types of terrorist attacks and provide important information for counter-terrorism work. The existing research on terrorist attacks only analyzes a few characteristics, which leads to the limitations of the research. Therefore, this paper not only adds some continuous and discrete features, but also adds unstructured features based on the current research, which can accurately describe terrorist attacks. This paper proposes a random forest method based on threshold for feature selection because of the added characteristics of terrorist attacks, and then uses XGBoost model to predict the types of terrorist attacks. This method helps to prevent terrorist attacks and reduce the damage caused by terrorist attacks, and provide decision support for the counter-terrorism department to take measures in advance.