Results 31 to 40 of about 2,461 (194)

A review on applied statistical and artificial intelligence techniques in crime forecasting [PDF]

open access: yes, 2019
Crime forecasting is an important component of crime analysis towards providing early information about possible crime occurrences in the future. Different models have been proposed to assess different crime data structures and representations.
Khairuddin, A. R., Haron, H., Alwee, R.
core   +1 more source

Hybrid Support Vector Regression and Autoregressive Integrated Moving Average Models Improved by Particle Swarm Optimization for Property Crime Rates Forecasting with Economic Indicators

open access: yesThe Scientific World Journal, 2013
Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and
Razana Alwee   +2 more
doaj   +1 more source

Forecasting prison populations using sentencing and arrest data [PDF]

open access: yes, 2013
Aim: To develop a method for forecasting the NSW remand and sentenced prisoner populations.Method: Autoregressive Integrated Moving Average (ARIMA) models with other time series as input variables were employed to estimate and forecast changes in the ...
Wai-Yin Wan
core  

Hybrid ARIMA-ANN for Crime Risk Forecasting: Enhancing Interpretability and Predictive Accuracy Through Socioeconomic and Environmental Indicators

open access: yesAlgorithms
As the demand for more accurate crime prediction and risk assessment grows, researchers have been developing smarter models that blend statistical methods with machine learning. This study compares a hybrid ARIMA-ANN model with traditional classification
Paul Iacobescu, Ioan Susnea
doaj   +1 more source

IDENTIFYING A PREDICTABLE PROPERTY CRIME TREND MODEL IN THE NORTH EAST OF ENGLAND [PDF]

open access: yes, 2010
This research examines the association of property crime sub-groups at police force district or basic command unit level, using official monthly police statistics and official claimant count (unemployment) data.
PITT, MARK,WILLIAM
core  

A Novel Multi-Module Approach to Predict Crime Based on Multivariate Spatio-Temporal Data Using Attention and Sequential Fusion Model

open access: yesIEEE Access, 2022
Forecasting crime is complex since several complicated aspects contribute to a crime. Predicting crime becomes more challenging because of the enormous number of everyday crime episodes in varied places. Though there are many established machine learning
Nowshin Tasnim   +2 more
doaj   +1 more source

CRIMINAL-POLITICAL FUTUROLOGY IN THE FIELD OF FIGHTING CRIME (CONCEPTUAL AND SUBJECT AREA) [PDF]

open access: yesKrymskij Naučnyj Vestnik, 2015
The article considers the subject area of the new direction of pre-vision — criminal-political futurology (forecasting) in the field of combating crime, absorbing in itself the main types of legal prediction: criminological, criminal, criminal Executive,
Valery Novichkov
doaj  

ACSAformer: A crime forecasting model based on sparse attention and adaptive graph convolution

open access: yesFrontiers in Physics
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   +9 more
doaj   +1 more source

Enhance interval width of crime forecasting with ARIMA model-fuzzy alpha cut

open access: yes, 2019
With qualified data or information a better decision can be made. The interval width of forecasting is one of data values to assist in the selection decision making process in regards to crime prevention.
Triana, Yaya Sudarya; Universitas Mercu Buana   +1 more
core   +2 more sources

Deep Learning for Crime Forecasting of Multiple Regions, Considering Spatial–Temporal Correlations between Regions

open access: yesEngineering Proceedings
Crime forecasting has gained popularity in recent years; however, the majority of studies have been conducted in the United States, which may result in a bias towards areas with a substantial population.
Martín Solís   +1 more
doaj   +1 more source

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