Artificial Neural Network System for Classification of Offenders in Murder and Rape Cases

摘要

When a serial offender strikes, it usually means that the investigation is unprecedented for that police agency. The volume of incoming leads and pieces of information in the case(s) can be overwhelming as evidenced by the thousands of leads gathered in the Ted Bundy Murders, Atlanta Child Murders, and the Green River Murders. Serial cases can be long-term investigations in which the suspect remains unknown and continues to perpetrate crimes. With state and local murder investigative systems beginning to crop up, it will become important to manage that information in a timely and efficient way by developing computer programs to assist in that task. One vital function will be to compare violent crime cases from different jurisdictions so investigators can approach the investigation knowing that similar cases exist. The Artificial Neural Network System for Classification of Offenders in Murder and Rape Cases project developed two software prototypes that demonstrate developed algorithms for analyzing and comparing large databases of crime data. The CATCH (Computer Aided Tracking and Characterization of Homicides) and CATCHRAPE software applications analyses homicide data and sexual assault data, respectively. Both applications are similar, although they analyze different databases.