Crime Prediction Modeling
Crime prediction modeling forecasts where and when crime is most likely to occur next, so that limited resources can be directed before incidents happen rather than after. It spans simple historical hot-spot extrapolation, statistical self-exciting point processes that treat crimes as triggering further crimes, and modern machine-learning models that blend spatial, temporal, and environmental features. The statistical foundation was sharpened by Mohler and colleagues' 2011 demonstration that earthquake-style self-exciting (Hawkes) point processes — in which each crime raises the short-term risk of nearby crimes — forecast urban crime more accurately than conventional hot-spot maps.
पूरी विधि पढ़ें
यह खंड पढ़ने के लिए निःशुल्क खाते से साइन इन करें।
पद्धति मानचित्र
सम्बन्धित पद्धतियों का परिवेश — अन्वेषण हेतु किसी नोड का चयन करें।
स्रोत
- Mohler, G. O., Short, M. B., Brantingham, P. J., Schoenberg, F. P., & Tita, G. E. (2011). Self-exciting point process modeling of crime. Journal of the American Statistical Association, 106(493), 100–108. DOI: 10.1198/jasa.2011.ap09546 ↗
- Perry, W. L., McInnis, B., Price, C. C., Smith, S. C., & Hollywood, J. S. (2013). Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations. RAND Corporation. ISBN: 9780833081483
इस पृष्ठ का उद्धरण कैसे दें
ScholarGate. (2026, June 22). Predictive Modeling of Crime Risk (Predictive Policing). ScholarGate. https://scholargate.app/hi/criminology/crime-prediction-modeling
कौन-सी पद्धति?
इस पद्धति को उसकी निकटतम सजातीय पद्धतियों के साथ रखकर उन्हें साथ-साथ पढ़ें — पुस्तकालय पुस्तकें मेज़ पर रख देता है; चुनाव आपका है।
- Crime Hot Spot AnalysisCriminology↔ तुलना करें
- Crime MappingCriminology↔ तुलना करें
- Near-Repeat AnalysisCriminology↔ तुलना करें
- Risk Terrain Modeling (Criminology)Criminology↔ तुलना करें