Hybrid of deep learning and exponential smoothing for enhancing crime forecasting accuracy. [PDF]
The continued urbanization poses several challenges for law enforcement agencies to ensure a safe and secure environment. Countries are spending a substantial amount of their budgets to control and prevent crime.
Umair Muneer Butt +3 more
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A systematic review on spatial crime forecasting [PDF]
Background Predictive policing and crime analytics with a spatiotemporal focus get increasing attention among a variety of scientific communities and are already being implemented as effective policing tools.
Ourania Kounadi +3 more
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Crime forecasting: a machine learning and computer vision approach to crime prediction and prevention [PDF]
A crime is a deliberate act that can cause physical or psychological harm, as well as property damage or loss, and can lead to punishment by a state or other authority according to the severity of the crime.
Neil Shah, Nandish Bhagat, Manan Shah
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Crime and violation are the threat to justice and meant to be controlled. Accurate crime prediction and future forecasting trends can assist to enhance metropolitan safety computationally. The limited ability of humans to process complex information from
Sohail Asghar, Wajiha Safat
exaly +3 more sources
Lightweight deep learning model for crime pattern recognition based on transformer with simulated annealing sparsity and CNN [PDF]
This study addresses the pressing need for high efficiency and low resource consumption in crime pattern recognition within public safety governance by proposing a lightweight deep learning model known as the lightweight crime recognition network (LCRNet)
HongYuan Lu +3 more
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ACSAformer: A crime forecasting model based on sparse attention and adaptive graph convolution
IntroductionCrime forecasting is crucial for urban safety management, as it facilitates the optimization of police resource allocation, crime prevention, and the enhancement of public security.
Zhenkai Qin
exaly +3 more sources
Money laundering rate modelling
The article continues the analysis of the work of the model developed by the authors of forecasting money laundering rate. The purpose of the study is to compare the results of the forecast with the actual data. Authors used official data by the Ministry
J. M. Beketnova, E. S. Anisimov
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Predicting Crime and Other Uses of Neural Networks in Police Decision Making
Neural networks are a machine learning method that excel in solving classification and forecasting problems. They have also been shown to be a useful tool for working with big data oriented environments such as law enforcement.
Steven Walczak
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Prostitution Arrest Spatial Forecasting in an Era of Increasing Decriminalization
There is ongoing debate regarding the merits of decriminalization or outright legalization of commercial sex work in the United States. A few municipalities have officially legalized both the selling and purchasing of sex, while others unofficially ...
Edward Helderop +3 more
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Big data analytics and smart cities: applications, challenges, and opportunities
Urban environments continuously generate larger and larger volumes of data, whose analysis can provide descriptive and predictive models as valuable support to inspire and develop data-driven Smart City applications.
Eugenio Cesario
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