A Survey of Research into Artificial Neural Networks for Crime Prediction
Crime is a complex social phenomenon, entirely determined by the contradictions of social processes interacting with one another and of criminogenic, anti-criminogenic and social phenomena, constantly changing in time and space. As a systematic stage in the fight against crime, the article seeks to review the methods used for predicting the level of crime occurrence based on artificial neural networks. The review of multiple prediction levels and methods to identify the time and place of the next crime is made. The study has focused on the articles from the previous 8 years to review the methods. The analysis found that the most common methods used by the researchers are deep crime network framework, convolutional network, neural network, multi-model data and the existing forecasting method. The made it possible to explore the previous forecasting methods used by the researchers to predict the crime level using the neural network.