Uncertain crime data analysis using hybrid approach

Modern criminal investigations include various cutting-edge scientific methods, including hybrid models, game theory, and machine learning. Criminal investigations consist of the examination of data that is utilized as evidence. In this sense, many significant and innovative studies on the crime uncertainty research of criminals have been carried out in the past, and one method for resolving this ambiguity is called Neutrosophic logic. The criminal in the crime application platform's initial inquiry may be a new involved or a previous offender. In this paper, the framework describes identifying offenders in a criminal investigation. Crime data for a wide range of offences were collected. This approach uses a game theory model to compare the present crime to previous crimes committed by the same individual. Making the right decision about the crime and exercising sound judgment depend on identifying the actual offender. When assessing the empirical data, taking in the incident's location and early criminal prediction is essential.