Open AccessFeatures of statistical modeling and forecasting of crime: theoretical aspect
Author(s) -
A. M. Terekhov,
Sergey Kuvychkov,
Sergey Smirnov
Publication year - 2021
Publication title -
ûridičeskaâ nauka i praktika
Language(s) - English
Resource type - Journals
ISSN - 2078-5356
DOI - 10.36511/2078-5356-2021-2-123-130
Subject(s) - law enforcement , econometric model , computer science , enforcement , crime analysis , completeness (order theory) , quality (philosophy) , state (computer science) , econometrics , economics , criminology , political science , sociology , machine learning , law , mathematics , mathematical analysis , philosophy , epistemology , algorithm
The purpose of the work is to provide a theoretical analysis of modern methods of modeling and forecasting the state of crime, which can be used in the system of public administration of the law enforcement sphere. In the course of the research, the peculiarities of using various tools and models for predicting the state of crime are revealed. A significant part of the research of scientists is directed towards the use of spatial and spatiotemporal models, as well as methods of artificial intelligence. The high quality of monthly forecasts is noted. Various economic, social, geographical, temporal and other groups of factors that influence the state of crime are identified. It is established that the quality of the developed crime forecasts depends on the choice of the optimal method and period of forecasting, on the completeness of the information base, including social, economic, legal and other characteristics of the phenomena and processes of public life that affect the criminal situation. It is noted that the practical use of artificial intelligence and econometric analysis methods in predicting the state of crime is becoming particularly relevant at the present time.