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http://dx.doi.org/10.9708/jksci.2012.17.4.163

A study of improved ways of the predicted probability to criminal types  

Chung, Young-Suk (Dept. of Computer Science & Engineering, Kongju national University)
Kim, Jin-Mook (Dept. of IT Education, Sun moon University)
Park, Koo-Rack (Dept. of Computer Science & Engineering, Kongju national University)
Publication Information
Journal of the Korea Society of Computer and Information / v.17, no.4, 2012 , pp. 163-172 More about this Journal
Abstract
Modern society, various great strength crimes are producing. After all crimes happen, it is most important that prevent crime beforehand than that cope. So, many research studied to prevent various crime. However, existing method of studies are to analyze and prevent by society and psychological factors. Therefore we wishes to achieve research to forecast crime by time using Markov chain method. We embody modelling for crime occurrence estimate by crime type time using crime occurrence number of item data that is collected about 5 great strength offender strength, murder, rape, moderation, violence. And examined propriety of crime occurrence estimate modelling by time that propose in treatise that compare crime occurrence type crime occurrence estimate price and actuality occurrence value. Our proposed crime occurrence estimate techniques studied to apply maximum value by critcal value about great strength crime such as strength, murder, rape etc. actually, and heighten crime occurrence estimate probability by using way to apply mean value about remainder crime in this paper. So, we wish to more study about wide crime case and as the crime occurrence estimate rate and actuality value by time are different in crime type hereafter applied examples investigating.
Keywords
Simulation; Crime statistics; Predictive modeling; Markov chains;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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