Predicting the geo-temporal variations of crime and disorder

Corcoran, Jonathan J., Wilson, Ian D. and Ware, J. Andrew (2003) Predicting the geo-temporal variations of crime and disorder. International Journal of Forecasting, 19 4: 623-634. doi:10.1016/S0169-2070(03)00095-5

Author Corcoran, Jonathan J.
Wilson, Ian D.
Ware, J. Andrew
Title Predicting the geo-temporal variations of crime and disorder
Journal name International Journal of Forecasting   Check publisher's open access policy
ISSN 0169-2070
Publication date 2003-10-01
Sub-type Article (original research)
DOI 10.1016/S0169-2070(03)00095-5
Volume 19
Issue 4
Start page 623
End page 634
Total pages 12
Place of publication Amsterdam, The Netherland
Publisher International Institute of Forecasters
Language eng
Subject 1205 Urban and Regional Planning
Abstract Traditional police boundaries—precincts, patrol districts, etc.—often fail to reflect the true distribution of criminal activity and thus do little to assist in the optimal allocation of police resources. This paper introduces methods for crime incident forecasting by focusing upon geographical areas of concern that transcend traditional policing boundaries. The computerised procedure utilises a geographical crime incidence-scanning algorithm to identify clusters with relatively high levels of crime (hot spots). These clusters provide sufficient data for training artificial neural networks (ANNs) capable of modelling trends within them. The approach to ANN specification and estimation is enhanced by application of a novel and noteworthy approach, the Gamma test (GT).
Keyword Crime forecasting
Cluster analysis
Geographic information system
Artificial neural networks
Gamma test
Autoregressive model
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Unknown
Additional Notes Special Issue on Crime Forecasting

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
School of Geography, Planning and Environmental Management Publications
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Citation counts: TR Web of Science Citation Count  Cited 28 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 35 times in Scopus Article | Citations
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Created: Wed, 17 Mar 2010, 21:24:00 EST by Ms Lynette Adams on behalf of Faculty of Science