Results 41 to 50 of about 2,461 (194)

Empirical Discriminative Tensor Analysis for Crime Forecasting [PDF]

, 2011
Police agencies have been collecting an increasing amount of information to better understand patterns in criminal activity. Recently there is a new trend in using the data collected to predict where and when crime will occur. Crime prediction is greatly beneficial because if it is done accurately, police practitioner would be able to allocate ...
Yang Mu, Wei Ding 0003, Melissa Morabito, Dacheng Tao   +3 more
openaire   +1 more source

HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting

, 2022
The goal of the crime forecasting problem is to predict different types of crimes for each geographical region (like a neighborhood or censor tract) in the near future.
Lin, Zongyu, Wang, Chenyu, Shahabi, Cyrus, Yue, Mingxuan, Yang, Xiaochen, Sun, Jiao   +5 more
core   +1 more source

Systematic review and meta-analysis of risk terrain modelling (RTM) as a spatial forecasting method

Crime Science, 2021
Background Several studies have tested the reliability of Risk Terrain Modelling (RTM) by focusing on different geographical contexts and types of crime or events.
Zoe Marchment, Paul Gill
doaj   +1 more source

Multi-density crime predictor: an approach to forecast criminal activities in multi-density crime hotspots

Journal of Big Data
The increasing pervasiveness of ICT technologies and sensor infrastructures is enabling police departments to gather and store increasing volumes of spatio-temporal crime data.
Eugenio Cesario, Paolo Lindia, Andrea Vinci   +2 more
doaj   +1 more source

Learning to rank spatio-temporal event hotspots

Crime Science, 2020
Background Crime, traffic accidents, terrorist attacks, and other space-time random events are unevenly distributed in space and time. In the case of crime, hotspot and other proactive policing programs aim to focus limited resources at the highest risk ...
George Mohler, Michael Porter, Jeremy Carter, Gary LaFree   +3 more
doaj   +1 more source

Deep Learning for Real Time Crime Forecasting

CoRR, 2017
4 pages, 6 figures, NOLTA ...
Wang, Bao, Zhang, Duo, Zhang, Duanhao, Brantingham, P, Bertozzi, Andrea L   +4 more
openaire   +4 more sources

Advances in forecasting with artificial neural networks [PDF]

, 2010
There is decades long research interest in artificial neural networks (ANNs) that has led to several successful applications. In forecasting, both in theoretical and empirical works, ANNs have shown evidence of good performance, in many cases ...
Crone, S, Kourentzes, N
core  

(Looking) Back to the Future: using space-time patterns to better predict the location of street crime

, 2009
Crime analysts attempt to identify regularities in police recorded crime data with a central view of disrupting the patterns found. One common method for doing so is hotspot mapping, focusing attention on spatial clustering as a route to crime reduction (
Tompson, Lisa, Michael Townsley, Townsley, M, Townsley, Michael, Lisa Tompson, Tompson, L   +5 more
core   +1 more source

Enhancing Multi-Level Spatio-Temporal Forecasting of Adjudicated Crime Occurrence Trends in Indonesia

Information
Indonesia faces persistent challenges in crime forecasting and judicial resource management, compounded by chronic underreporting and inconsistent spatial resolution in official crime statistics.
Firman Arifman, Teddy Mantoro, Media Anugerah Ayu   +2 more
doaj   +1 more source

Parameter optimization of gradient tree boosting using dragonfly algorithm in crime forecasting and analysis [PDF]

, 2019
Crime forecasting and analysis are very important in predicting future crime patterns and beneficial to the authorities in planning effective crime prevention measures.
Zain, A. M., Khairuddin, A. R., Ali, N. A., Haron, H., Alwee, R.   +4 more
core   +1 more source