Results 21 to 30 of about 1,668 (256)

Forecasting Crime Using ARIMA Model

CoRR, 2020
Data mining is the process in which we extract the different patterns and useful Information from large dataset. According to London police, crimes are immediately increases from beginning of 2017 in different borough of London. No useful information is available for prevent crime on future basis.
Khawar Islam, Akhter Raza
openaire   +2 more sources

Predicting density of serious crime incidents using a Multiple-Input Hidden Markov Maximization a posteriori model

Machine Learning with Applications, 2022
Accurately predicting the displacement of crime from a given state such as cold to another state such as warm or hot, facilitates the efficient allocation of resources and the mitigation of crime threats.
Devon L. Robertson, Wayne A. Goodridge
doaj   +1 more source

Local deprivation predicts right-wing hate crime in England.

PLoS ONE, 2023
We argue that community deprivation can increase the risk of right-wing radicalization and violent attacks and that measures of local deprivation can help improve forecasting local hate crime rates.
Margherita Belgioioso, Christoph Dworschak, Kristian Skrede Gleditsch   +2 more
doaj   +1 more source

Incorporating Survey Perceptions of Public Safety and Security Variables in Crime Rate Analyses for the Visegrád Group (V4) Countries of Central Europe

Societies, 2022
Public governance has evolved in terms of safety and security management, incorporating digital innovation and smart-analytics-based tools to visualize abundant data collections. Urban safety and security are vital social problems that have many branches
Usman Ghani, Peter Toth, Dávid Fekete
doaj   +1 more source

THE IMPACT OF THE CRIME RATE ON THE HOSPITALITY AND TOURISM INDUSTRY IN THE EU COUNTRIES [PDF]

Geo Journal of Tourism and Geosites, 2023
Tourism is the largest service industry in the world. The direct and reverse relationship between crime and tourism significantly affects the economy, society and individuals.
Rostyslav SHCHOKIN, Vitaliy MAZIYCHUK, Oleksandr MYKHAILYK, Alina KOLOMIIETS, Svitlana AKIFZADE, Yuriy TYMOSHENKO   +5 more
doaj   +1 more source

Comparing Machine Learning-Based Crime Hotspots Versus Police Districts: What’s the Best Approach for Crime Forecasting?

IEEE Access
Criminal activity poses a significant challenge in urban environments, impacting public safety, economic stability, and overall quality of life. As a result, the efficient allocation of public security resources based on spatio-temporal crime prediction ...
Eugenio Cesario, Paolo Lindia, Andrea Vinci   +2 more
doaj   +1 more source

Enhancing Spatial-Temporal Crime Forecasting Using Machine Learning for Law Enforcement

IEEE Access
Traditional crime forecasting often lacks the granularity and adaptability required to address evolving spatial and temporal crime patterns. Standard reactive models may fail to capture the complex, non-linear dynamics of urban crime, leaving law ...
Nanan Soekarna, Teddy Mantoro, Umar Aditiawarman, Firman Arifman, Ben Rahman   +4 more
doaj   +1 more source

Rotational grid, PAI‐maximizing crime forecasts

Statistical Analysis and Data Mining: The ASA Data Science Journal, 2018
Crime forecasts are sensitive to the spatial discretizations on which they are defined. Furthermore, while the Predictive Accuracy Index (PAI) is a common evaluation metric for crime forecasts, most crime forecasting methods are optimized using maximum likelihood or other smooth optimization techniques. Here we present a novel methodology that jointly (
George O. Mohler, Michael D. Porter
openaire   +3 more sources

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

Algorithms
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

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

The 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, Siti Mariyam Hj Shamsuddin, Roselina Sallehuddin   +2 more
doaj   +1 more source