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Articles de revues sur le sujet « Crime hotspot »

Auteur : Grafiati

Publié le 2 juin 2025

Mis à jour le 31 juillet 2025

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1

Ajide, Oyinloye M., and Olamiju I. Oluwadare. "Mapping Crime Hotspots in Akure, Nigeria: A GIS Perspective." Urban Studies and Public Administration 1, no. 1 (2018): 135. http://dx.doi.org/10.22158/uspa.v1n1p135.

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<p><em>African countries in recent times have witnessed an unprecedented level of insecurity. This has made national security threat to be a major issue for the government and has prompted huge allocation of the national budget to security. The objective of this paper is to mark out crime hotspot areas in the central area of Akure metropolis; and examine the rate at which crimes are committed, the surveillance method used and its effectiveness. The research made use of Google Earth imagery and Geographical Information System (GIS) technology to delineate crime hotspots in Akure. A

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Hart, Timothy C. "Investigating Crime Pattern Stability at Micro-Temporal Intervals: Implications for Crime Analysis and Hotspot Policing Strategies." Criminal Justice Review 46, no. 2 (2021): 173–89. http://dx.doi.org/10.1177/0734016821996785.

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Studies of crime hotspot forecasts use various metrics to describe different characteristics of prediction patterns. However, few investigations consider how the stability of crime hotspot, estimated at relatively short temporal intervals, can impact hotspot policing efforts. In response, using address-level incident location data that were collected from six law enforcement agencies in the United States, the current study examines the daily stability of crime hotspots that were estimated over a 1-year period. Results suggest that micro-temporal stability patterns in crime hotspot forecasts ar

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He, Zhanjun, Rongqi Lai, Zhipeng Wang, Huimin Liu, and Min Deng. "Comparative Study of Approaches for Detecting Crime Hotspots with Considering Concentration and Shape Characteristics." International Journal of Environmental Research and Public Health 19, no. 21 (2022): 14350. http://dx.doi.org/10.3390/ijerph192114350.

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Hotspot detection is an important exploratory technique to identify areas with high concentrations of crime and help deploy crime-reduction resources. Although a variety of methods have been developed to detect crime hotspots, few studies have systematically evaluated the performance of various methods, especially in terms of the ability to detect complex-shaped crime hotspots. Therefore, in this study, a comparative study of hotspot detection approaches while simultaneously considering the concentration and shape characteristics was conducted. Firstly, we established a framework for quantitat

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Mei, Linfeng, and Juncheng Wei. "The existence and stability of spike solutions for a chemotax is system modeling crime pattern formation." Mathematical Models and Methods in Applied Sciences 30, no. 09 (2020): 1727–64. http://dx.doi.org/10.1142/s0218202520500359.

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Urban crime such as residential burglary is a social problem in every major urban area. As such, many mathematical models have been proposed to study the collective behavior of these crimes. In [V. B. Pasour, G. E. Tita, P. J. Brantingham, A. L. Bertozzi, M. B. Short, M. R. D’Orsogna and L. B. Chayes, A statistical model of crime behavior, Math. Methods Appl. Sci 107 (2008) 1249–1267; M. B. Short, A. L. Bertozzi and P. J. Brantingham, Nonlinear patterns in urban crime: Hotspots, bifurcations, and suppression, SIAM J. Appl. Dyn. Syst. 9 (2010) 462–483], Short et al. proposed an agent-based stat

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Soppari, Dr Kavitha. "City Crime Hotspot Identification and Visualization Development of a Web Application for Improving Urban Safety and Decision Making." International Scientific Journal of Engineering and Management 04, no. 05 (2025): 1–7. https://doi.org/10.55041/isjem03400.

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Abstract: Urban crime hotspots present significant challenges to public safety and effective city planning. This study proposes a web-based crime hotspot identification and visualization system that utilizes geospatial mapping, machine learning, and data analytics. The application empowers law enforcement agencies and policymakers by classifying high-risk areas, tracking evolving crime trends, and predicting future crime occurrences. The system’s interactive dashboard delivers real-time, data-driven insights to support strategic decision-making and improve urban safety outcomes. Keywords: Crim

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Debata, Ipsita, Prem Sagar Panda, E. Karthikeyan, et al. "Spatial auto-correlation and endemicity pattern analysis of crimes against children in Tamil Nadu from 2017 to 2021." Journal of Family Medicine and Primary Care 13, no. 6 (2024): 2341–47. http://dx.doi.org/10.4103/jfmpc.jfmpc_1463_23.

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ABSTRACT Background: A child is a nation’s supreme asset and future. India homes 444 million children, aged between 0 and 18 years, contributing to 19% of the world’s children. Crime against children is detrimental to their mental and physical health and affects their growth and development. The National Crime Record Bureau recently reported that a crime targeting children happens every 4 minutes. There is a paucity of literature regarding the burden of crime against children. To understand the magnitude and spatial distribution of crime against children, a retrospective surveillance study was

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Chainey, Spencer P., Sophie J. Curtis-Ham, R. Mark Evans, and Gordon J. Burns. "Examining the extent to which repeat and near repeat patterns can prevent crime." Policing: An International Journal 41, no. 5 (2018): 608–22. http://dx.doi.org/10.1108/pijpsm-12-2016-0172.

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Purpose The purpose of this paper is to examine the extent and variation in the estimates to which crime can be prevented using patterns of repeats and near repeats, and whether hotspot analysis complements these patterns. Design/methodology/approach Crime data for four study areas in New Zealand are used to examine differences in the extent of burglary repeat and near repeat victimisation. Hotspots of burglary are also created to determine the extent to which burglary repeats and near repeats spatially intersect hotspots. Findings The extent of repeats and near repeats varies, meaning there i

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Rajapandian, Mr P. "Enhanced Crime Hotspot Prediction and Visualization for Women’s Safety Through Deep Learning." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49726.

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Abstract- Crime hotspots are geographic areas with elevated levels of criminal activities compared to other regions. Women in these hotspots are at increased risk of experiencing various forms of criminal behavior, including sexual harassment, assault, domestic violence, stalking, and human trafficking. Identifying these hotspots is crucial for effective crime prevention and resource allocation by law enforcement agencies. This project presents Safety Locator, a predictive system that uses multimodal deep learning to identify and map crime hotspots where women are particularly vulnerable. The

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Nakamura, Hiroki, and Shunsuke Managi. "Why does perceive safety endure in crime hotspots? Case of Delhi." Safer Communities 19, no. 4 (2020): 183–98. http://dx.doi.org/10.1108/sc-02-2020-0006.

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Purpose Using a case study from Delhi, India, this study aims to investigate why perceived safety endures despite crimes in the neighborhood. Local residents in Delhi feel considerably less fearful of crime in their neighborhoods, and a majority reported feeling safe in their neighborhoods, especially during the daytime. Design/methodology/approach This paper hypothesized that similar to the crime itself, perceptions of safety or the fear of crime, also tend to be concentrated in hotspots. Following a hotspot analysis based on the respondents’ perceptions of safety, the data gathered were appl

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Redzuan, Mohd Sofian, Tarmiji Masron, Syahrul Nizam Junaini, et al. "Urban Violent Crime Dynamics in Kuala Lumpur and Putrajaya: Utilizing Spatial Temporal Techniques." Forum Geografi 39, no. 1 (2025): 1–19. https://doi.org/10.23917/forgeo.v39i1.6456.

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This paper investigates the patterns of violent crime in Kuala Lumpur and Putrajaya between 2015 and 2020 using advanced spatial analysis techniques, including Spatial Autocorrelation, Standard Deviational Ellipse (SDE), and Mean Centre (MC). The study analyses the spatial distribution and temporal dynamics of violent crimes, tracks shift in crime hotspots and examines the influence of socio-economic factors on these patterns. Findings reveal that violent crimes predominantly occurred in the late afternoon and night, with peak incidents at 3:00 PM (1,830 cases, 8.28%). The study highlights not

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Heredia G., Lenin, and Germán E. Bravo C. "Using Hotspots Algebra to analyze crime events and their urban context." Revista Colombiana de Computación 18, no. 1 (2017): 9–26. http://dx.doi.org/10.29375/25392115.3202.

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Hotspots analysis is essential in the criminology field and quite important in decisions making for police agencies because it permits the enhancement of allocation of police resources for timely and adequate actions. There exist different techniques for analysis and generation of hotspots, limited by its difficulty to consider other urban and demographic factors that could be the cause of the emergence of these hotspots or their influence over other factors. On the other hand, it is also difficult and unusual to analyze hotspots in a temporal context. This paper seeks, through spatial-tempora

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Sejal, Suryawanshi. "Crime Predictive Model for Hotspot Mapping." International Journal for Research in Applied Science and Engineering Technology 12, no. 6 (2024): 1306–11. http://dx.doi.org/10.22214/ijraset.2024.63305.

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Abstract: In contemporary law enforcement, the need for proactive strategies to combat crime and ensure public safety is paramount. This paper presents the development and implementation of a predictive modeling framework aimed at identifying crime hotspots and optimizing resource allocation for law enforcement agencies. The model leverages historical crime data, geographical information, and socio- economic factors to forecast areas at elevated risk of criminal activity. Through a multistage process encompassing data collection, preprocessing, feature engineering, and model training, the pred

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Dodo, Boubakar, Umar Usman, B. K. Asare, and Y. M. Ahijjo. "A Geospatial Analysis of Crimes Patterns in Niger Republic Using Hotspots and K-Means Cluster." UMYU Scientifica 4, no. 2 (2025): 158–74. https://doi.org/10.56919/usci.2542.018.

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Study’s Excerpt:• Crime patterns in Niger were analyzed using crime maps and k-means clustering techniques.• 61.53% of crime hotspots are in the west, bordering Mali, Burkina Faso, and Benin Republic.• Southern regions (33.33%) face crimes like rebellion and counterfeiting near Nigeria's border.• Northern hotspots (15.38%) show illegal arms and corruption near Libya, Chad, and Algeria.• Study suggests cross-border security and optimized law enforcement in high-crime clusters.Full Abstract:This study is an investigation of some crimes in the Niger Republic. The methods consist of determining th

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Sritha, Zith Dey Babu. "Temporal and Spatial Crime Hotspot Verdict: An Introduction." International Journal of Technology Information and Computer (TIJOTIC) 1, no. 1 (2020): 1–7. https://doi.org/10.5281/zenodo.3861881.

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The storage and analysis of criminal databases, undebatable, is an essential program. To intuiting the crime, we need to find the map and create some hotspots there. Crime investigation system is a challenging process for every police or detectives to finalize the primary target. Sometimes the polices or investigators are unable to reach the main goal or criminal. To contact the primary goal, we need to validate the temporal and spatial hotspots among the crimes arena. It’s crucial to find the main criminal to protect the world, although it’s not very easy to find the big fish. Bec

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Ojeh, Vincent Nduka, Mohammed Bakoji Yusuf, Mohammed Abdullahi, Nicodemus Bongnwi John, Auwal Bakaku, and Kafando Halidou. "Crime hotspots and its effect on socio-economic activities using Geographical Information System (GIS) in 3 selected local government areas in northern Taraba, Nigeria." Eco Cities 4, no. 2 (2024): 2386. http://dx.doi.org/10.54517/ec.v4i2.2386.

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<p>This study examines crime hotspots in Northern Taraba, Taraba State, Nigeria, using GIS. The prevalence of crime has escalated in Nigeria and Taraba State, especially in the northern region, where Jalingo, the state capital, is situated. The study focused on identifying crime hotspots in Northern Taraba and assessing the socio-economic consequences associated with high crime rates in the study area. The data was acquired from the field and from the Nigerian Police Force. The findings indicate that the most prevalent offenses are theft (20.9%) and thuggery/cultism (12.9%). The study pe

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Haider, Mohammad Ali, and Pawinee Iamtrakul. "Analyzing Street Crime Hotspots and Their Associated Factors in Chittagong City, Bangladesh." Sustainability 14, no. 15 (2022): 9322. http://dx.doi.org/10.3390/su14159322.

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Urban street crime (USC) hotspots severely affect the residential and business neighborhood (RBN) areas of any urban center. This study analyzes USC hotspots and identifies the associated risk factors of becoming a USC hotspot in the residential and business neighborhood areas of Chittagong city. Primary and secondary data sources were used, but primary data played a primary role in this study. It was found that male, married, landlord, and middle-income groups of people are more likely to be victimized than the female, unmarried, renters, rich, and no-income groups. More street crime hotspots

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TSE, W. H., and M. J. WARD. "Hotspot formation and dynamics for a continuum model of urban crime." European Journal of Applied Mathematics 27, no. 3 (2015): 583–624. http://dx.doi.org/10.1017/s0956792515000376.

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The existence, stability, and dynamics of localized patterns of criminal activity are studied for the reaction–diffusion model of urban crime introduced by Short et al. (Math. Models. Meth. Appl. Sci.18(Suppl.), (2008), 1249–1267). In the singularly perturbed limit of small diffusivity ratio, this model admits hotspot patterns, where criminal activity of high amplitude is localized within certain narrow spatial regions. By using a combination of asymptotic analysis and numerical path-following methods, hotspot equilibria are constructed on a finite 1-D domain and their bifurcation properties a

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Tobias, Chitani Jarves Bob, and Brave Mwanza. "Spatial and Temporal Analysis: A GIS-Based Application Tool for Crime Monitoring and Clustering in Malawi." European Scientific Journal, ESJ 20, no. 8 (2024): 167. http://dx.doi.org/10.19044/esj.2024.v20n8p167.

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For the purposes of monitoring, evaluating, and conducting a geographical analysis of crime-related data, the study used geospatial technology to collect crime data based on spatial location and the Malawi Police Data Digest of 2019 and 2020. In a more generic sense, knowing the geographic patterns of crime in Malawi using GIS technology can help determine how to make and implement important decisions to reduce crimes in Malawi. The Malawi Police Service has established a number of database management systems to help with crime monitoring. Notwithstanding, it has not yet fully integrated Geogr

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D G, Kavyashree, and Amruth M M. "Crime Trends Analysis." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–8. https://doi.org/10.55041/ijsrem.spejss010.

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Abstract—Crime has become a growing concern in urban and rural regions alike, posing significant challenges to law enforcement agencies and policymakers. The analysis and forecasting of crime rates through data-driven methods is the main topic of this paper. This study intends to uncover crime patterns, hotspot regions, and temporal trends by utilizing statistical approaches, machine learning techniques, and historical crime data. The system integrates real-time data (where available) and uses predictive models to forecast the likelihood of various types of crimes in specific areas. The primar

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D G, Kavyashree, and Ajay Kumar M. "Criminal Incidence Rate." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–7. https://doi.org/10.55041/ijsrem.spejss013.

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Abstract—Crime has become a growing concern in urban and rural regions alike, posing significant challenges to law enforcement agencies and policymakers. The analysis and forecasting of crime rates through data-driven methods is the main topic of this paper. This study intends to uncover crime patterns, hotspot regions, and temporal trends by utilizing statistical approaches, machine learning techniques, and historical crime data. The system integrates real-time data (where available) and uses predictive models to forecast the likelihood of various types of crimes in specific areas. The primar

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BOYI MAIRIGA, Murna Joy Dawarga, Mustapha Yusuf, Taimanda Keren Ezekiel, Frichi Bilham, and Kabati Danjuma Madaki. "Crime mapping and hot spot analysis using geospatial data in Jalingo metropolis of Taraba State, Nigeria." World Journal of Advanced Research and Reviews 20, no. 1 (2023): 510–21. http://dx.doi.org/10.30574/wjarr.2023.20.1.2051.

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Crime mapping and hot spot analysis are topical and significant research across the fields of criminology, data digging, city planning and law enforcement for crime control. This study seeks to identify high crime areas which require an officer presence and predicting the possible response demand to increase the efficiency of response officer patrols. Crime type and patterns exist on a spatial level; these patterns and type can be grouped geographically by physical location, and analyzed contextually based on the region in which crime occurs. The study aimed at analyzing crime hotspots using g

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BOYI, MAIRIGA, Joy Dawarga Murna, Yusuf Mustapha, Keren Ezekiel Taimanda, Bilham Frichi, and Danjuma Madaki Kabati. "Crime mapping and hot spot analysis using geospatial data in Jalingo metropolis of Taraba State, Nigeria." World Journal of Advanced Research and Reviews 20, no. 1 (2023): 510–21. https://doi.org/10.5281/zenodo.12188283.

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Crime mapping and hot spot analysis are topical and significant research across the fields of criminology, data digging, city planning and law enforcement for crime control. This study seeks to identify high crime areas which require an officer presence and predicting the possible response demand to increase the efficiency of response officer patrols. Crime type and patterns exist on a spatial level; these patterns and type can be grouped geographically by physical location, and analyzed contextually based on the region in which crime occurs. The study aimed at analyzing crime hotspots using g

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Biralatei Fawei, Anderline Amaogbo, and Biriyai Diripigi Okolai. "Crime Rate Prediction System -An Experiment with Denver Crime Dataset Using Machine Learning Technique." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 4 (2024): 09–17. http://dx.doi.org/10.32628/cseit24104100.

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In recent years the nation Nigeria has experienced an increasing rate of criminality in the six geopolitical zones. Different crimes ranging from kidnapping, herdsmen attack, banditry, killings and so on. These activities have generated fear in the minds of the citizens thereby disrupting individuals, communities and their economic activities. This has affected both foreign and local investors in investing in the state. The overall effect on the socio-economic growth of the nation is unbearable. This paper presents a supervised machine learning technique for crime prediction using the Random F

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Philip Okoh Amodu, Jasini Ali Alwadood, Olaide Monsur Aderoju, et al. "A GIS-based analysis of open space and the likelihood of crime hotspot in Abuja city centre." World Journal of Advanced Research and Reviews 20, no. 3 (2023): 1303–13. http://dx.doi.org/10.30574/wjarr.2023.20.3.2500.

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In recent times, reported incidences of crimes in Abuja City Centre have taken a worrisome dimension with attendant socio-economic impacts including loss of lives and properties. The occurrence of some of these crimes are possible because of the presence of some open spaces around the crime locations. As cities grow, one feature that easily get altered is the open space. Some open spaces lose their original plans, others become abandoned and overgrown with bushes thus serving as hideouts for criminals. Open spaces play a major role in the development of modern cities and are usually prioritize

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Philip, Okoh Amodu, Ali Alwadood Jasini, Monsur Aderoju Olaide, et al. "A GIS-based analysis of open space and the likelihood of crime hotspot in Abuja city centre." World Journal of Advanced Research and Reviews 20, no. 3 (2023): 1303–13. https://doi.org/10.5281/zenodo.12773900.

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In recent times, reported incidences of crimes in Abuja City Centre have taken a worrisome dimension with attendant socio-economic impacts including loss of lives and properties. The occurrence of some of these crimes are possible because of the presence of some open spaces around the crime locations. As cities grow, one feature that easily get altered is the open space. Some open spaces lose their original plans, others become abandoned and overgrown with bushes thus serving as hideouts for criminals. Open spaces play a major role in the development of modern cities and are usually prioritize

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Mohammed Saifulla and G. Chandrakala. "Utilizing Machine Learning Ensemble Techniques for Crime Hotspot Analysis and Prediction." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 3 (2024): 136–45. http://dx.doi.org/10.32628/cseit2410313.

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By combining the predictions of trained classifiers, the ensemble learning approach generates new examples through cooperative decision-making. Evidence from early analysis has demonstrated the empirical and logical superiority of ensemble classifiers over single component classifiers. It is still difficult to identify the right configuration for a given dataset, even with the presentation of many ensemble approaches. Many theories based on prediction have been developed to address the topic of machine learning crime prediction in India. The dynamic character of crimes becomes difficult to asc

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Oh, Ha-Neul, and Seok-Jin Kang. "A Study on the Effect of Crime Displacement and Diffusion Effect of Crime Control in CPTED Projects." Korea CPTED Association 15, no. 1 (2024): 57–82. http://dx.doi.org/10.26470/jcssed.2024.15.1.57.

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In order to systematically analyze the effectiveness of the CPTED project, this study analyzed the crime prevention effect of the project as well as the effect of crime transfer and profit diffusion through WDQ analysis. The main results of the study are as follows. First, as a result of analyzing the crime prevention effect of the CPTED project, it was found that Site 1 decreased significantly compared to the upper administrative dong, but Site 2 decreased smaller than the upper administrative dong. As a result of the hotspot analysis before and after the project, Site 1's hotspot was reduced

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Chen, H., T. Cheng, and S. Wise. "DESIGNING DAILY PATROL ROUTES FOR POLICING BASED ON ANT COLONY ALGORITHM." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-4/W2 (July 10, 2015): 103–9. http://dx.doi.org/10.5194/isprsannals-ii-4-w2-103-2015.

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In this paper, we address the problem of planning police patrol routes to regularly cover street segments of high crime density (hotspots) with limited police forces. A good patrolling strategy is required to minimise the average time lag between two consecutive visits to hotspots, as well as coordinating multiple patrollers and imparting unpredictability in patrol routes. Previous studies have designed different police patrol strategies for routing police patrol, but these strategies have difficulty in generalising to real patrolling and meeting various requirements. In this research we devel

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Yadav, Kajal. "Crime Mapping and Forecasting Using Geospatial Techniques: A Case of Ajmer." International Journal for Research in Applied Science and Engineering Technology 11, no. 10 (2023): 1323–38. http://dx.doi.org/10.22214/ijraset.2023.56178.

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Abstract: Advances in computer technology, the development of GIS application software, and the ability to access various geographic data through open-source data sources have allowed police and law enforcement agencies to use it effectively. Crime mapping and spatial analysis using GIS tools such as hotspot generation, zoning, crime navigation and profiling, mobile location recognition, and various web applications are clearly recognized and can be scientifically applied to improve citizenship while being effectively used to predict and control crime. The present study analyzed the trends and

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Hart, Timothy, and Paul Zandbergen. "Kernel density estimation and hotspot mapping." Policing: An International Journal of Police Strategies & Management 37, no. 2 (2014): 305–23. http://dx.doi.org/10.1108/pijpsm-04-2013-0039.

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Purpose – The purpose of this paper is to examine the effects of user-defined parameters settings (e.g. interpolation method, grid cell size, and bandwidth) on the predictive accuracy of crime hotspot maps produced from kernel density estimation (KDE). Design/methodology/approach – The influence of variations in parameter settings on prospective KDE maps is examined across two types of interpersonal violence (e.g. aggravated assault and robbery) and two types of property crime (e.g. commercial burglary and motor vehicle theft). Findings – Results show that interpolation method has a considerab

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Maurya, Prakash, Tahir Shaikh, Imran Ahmed, Amaan Firdosi, and Prof Kiran Deshmukh. "Crime Analysis and Prediction Using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (2023): 1470–73. http://dx.doi.org/10.22214/ijraset.2023.50310.

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Abstract: The aim of this study is to develop a machine learning-based application that can analyze crime data across different districts in India and categorize them as high, moderate, or low based on the frequency of crimes. Based on the frequency of particular crimes in particular districts we will suggest necessary preventive measures and also recommend some precautions before visiting a particular crime hotspot. The methodology involved using a Logistic regression model for crime classification, followed by k-means clustering to group districts based on their crime rates. The results of t

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Zhang, Hong, Yongping Gao, Dizhao Yao, and Jie Zhang. "Interaction of Crime Risk across Crime Types in Hotspot Areas." ISPRS International Journal of Geo-Information 12, no. 4 (2023): 176. http://dx.doi.org/10.3390/ijgi12040176.

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Repeat and near-repeat victimization are important concepts in the study of crime. The incidence of repeat offenses within a single type of crime has been confirmed. However, the study of the circumstances existing across crime types requires further investigation. This article investigates whether the phenomenon of near-repeat crime exists in different types of crime by studying the spread of crime risk within different crime types. Taking Suzhou City as the research area, a DBSCAN-based algorithm is proposed, which can detect a large number of important and stable hotspots through the multi-

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Uglickich, Evženie, and Ivan Nagy. "3D Local Crime Type Models Based on Crime Hotspot Detection." Neural Network World 34, no. 2 (2024): 89–110. http://dx.doi.org/10.14311/nnw.2024.34.006.

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This paper deals with the analysis of the relationship between locations and types of crime observed in the Czech Republic. Cluster analysis of crime data based on the recursive Bayesian mixture estimation algorithm is used to identify crime hotspots and estimate local models of crime type. The experiments report that the 2D configuration of the algorithm allows the detection of crime hotspots online. The 3D configuration provides 29% more accurate crime type models than 2D clustering and alternative data mining algorithms. For the data set used, it was determined in which crime hotspots the m

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Wang, Tien-Chin, and Bi-Chao Lee. "Community security is the key to sustainable governance: Methods and functions of crime hotspot predictions." Corporate Governance and Sustainability Review 5, no. 2 (2021): 57–72. http://dx.doi.org/10.22495/cgsrv5i2p5.

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Forecasting is becoming increasingly important in corporate sustainability governance, as is government governance, and the prediction of police crime hotspots is related to human rights, so transparency is needed. There are many ways to predict hotspots of criminal activity in urban areas. Experts assume that if many crimes occur somewhere, even more, are likely to happen at subsequent times. Such predictions may rely on a state dependency model such as the Poisson distribution algorithm to formulate re-occurrence, its results can provide a visualized hotspot map with Q-GIS maps. Forecasting

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Chakraborty, Shima, Sadia Sharmin, and Fahim Irfan Alam. "Geospatial Crime Hotspot Detection: A Robust Framework using Birch Clustering Optimal Parameter Tuning." International journal of Web & Semantic Technology 16, no. 1 (2025): 01–13. https://doi.org/10.5121/ijwest.2025.16101.

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Crime causes physical and mental damage. Several crime prevention measures have been developed by law enforcement officials since they realized how serious this problem is. These preventative measures are not strong enough to help lower crime rates because they are typically slow-paced and ineffectual. In this regard, machine learning community has started developing automated approaches for detecting crime hotspot, after performing a careful analysis of the crime trend incorporating geospatial, temporal, demographic, or other relevant information. In this research, we look at detecting crime

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Archana, S., and R. Keren. "Crime Hotspot Mapping and Behavioral Analysis System." Research and Reviews: Advancement in Cyber Security 2, no. 3 (2025): 1–5. https://doi.org/10.5281/zenodo.15421539.

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<em>The Crime Hotspot Mapping and Behavioral Analysis System is designed to enhance public safety by leveraging data analytics, artificial intelligence, and geospatial technologies. This system aims to identify crime-prone areas through historical data patterns and visualize them on an interactive map, aiding law enforcement in proactive decision-making. It integrates behavioral analysis to assess potential threats and criminal tendencies, enabling predictive policing strategies. The system supports various stakeholders including police departments, civic authorities, and public policy makers

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Awodire, Moyosoluwa Akinpelu, Aminah Oluwakemi Momoh, Nelson Monteiro, and Tobiloba Adepoju. "Applying AI-Driven Predictive Policing: A Machine Learning Approach to Crime Prediction and Prevention." International Journal of Engineering and Computer Science 14, no. 06 (2025): 27317–39. https://doi.org/10.18535/ijecs.v14i06.5160.

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This study is intended to explore the use of machine learning models in predictive policing by using various methods to improve crime forecasting and prevention. Several combinations, such as the random forest, support vector machine (SVM), and neural network models, were used to predict the crime hotspot and its rate. To train and validate the models fed with a dataset of crime reports and demographic data, our outcomes proved that they predicted crime hotspots and rates sufficiently and quite well; random forest stood out as the best among them. These findings will inevitably have important

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Stanisław Mordwa. "(GIS Techniques) – In Search of Crime Hotspots." Archives of Criminology, no. XXXVII (January 1, 2015): 279–302. http://dx.doi.org/10.7420/ak2015i.

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Since the accomplishments of the social ecology school, it is common knowledge thatthere is a thesis about the existence of a strong relationship between crime and space. Since the 1990s, the police has been equipped with various GIS techniques which allowthe discovery of spatial patterns in the distribution of crime. The techniques turned outto be very helpful for effectively combating crime and misdemeanours, since the policewere in a position to identify small individual spaces in towns that were characterisedwith high crime indicators. These places are usually referred to as crime hotspots

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Bharti, Amisha, and Sonajharia Minz. "Getis-Ord (Gi*) based Farmer Suicide Hotspot Detection." Journal of Information Technology and Digital World 4, no. 2 (2022): 74–83. http://dx.doi.org/10.36548/jitdw.2022.2.002.

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Farmer suicidal hotspot detection proposed in this paper aims to reduce the death of the farmers. Using geographical information system is vital in predicting potential hotspots for farmer suicide. This study has collected and analyzed data on farmer suicide in India, using state-wise information from the National Crime Records Bureau and has determined the recent higher rate of farmer suicide. Spatial statistics analysis tools that address average nearest neighbor analysis has been used. Global analysis through Moran's Index, analyzed that the farmer suicides have a clustered pattern and plot

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BUTTENSCHOEN, ANDREAS, THEODORE KOLOKOLNIKOV, MICHAEL J. WARD, and JUNCHENG WEI. "Cops-on-the-dots: The linear stability of crime hotspots for a 1-D reaction-diffusion model of urban crime." European Journal of Applied Mathematics 31, no. 5 (2019): 871–917. http://dx.doi.org/10.1017/s0956792519000305.

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In a singularly perturbed limit, we analyse the existence and linear stability of steady-state hotspot solutions for an extension of the 1-D three-component reaction-diffusion (RD) system formulated and studied numerically in Jones et. al. [Math. Models. Meth. Appl. Sci., 20, Suppl., (2010)], which models urban crime with police intervention. In our extended RD model, the field variables are the attractiveness field for burglary, the criminal population density and the police population density. Our model includes a scalar parameter that determines the strength of the police drift towards maxi

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K. Kumaraswamy, P. Mary Santhi, S. Balaselvakumar,. "GEOINFORMATICS FOR PLACES OF CRIME OCCURRENCES IN TIRUCHIRAPPALLI CITY, TAMIL NADU." Psychology and Education Journal 58, no. 2 (2021): 5874–93. http://dx.doi.org/10.17762/pae.v58i2.3061.

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This study is an attempt to investigate the places of crime occurrences in Tiruchirappalli city. It reveals that the places of crime occurrences are not always the same as the places of residence of criminals. The maximum of automobile theft (38.7%) of (79 cases), in the areas of Theppakulam, Periyasamy Tower, Sarathas Kadai, Chattram Bus Stand and Priyakammla Street in Fort range, theft (36%) of (54 cases) in and around of Central Bus Stand and Edamalaipattipudur in Cantonment range. Most of the residences of criminals are located in the northwestern of Woraiyur and central parts of Palakkara

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Jibatswen Agbutsokwa Hosea, Eyong Eteng Eyong, Jagila Jantiku, et al. "Geospatial hotspots mapping of banditry/kidnapping in USSA and Takum local government area of Taraba state." World Journal of Advanced Research and Reviews 26, no. 3 (2025): 790–805. https://doi.org/10.30574/wjarr.2025.26.3.2238.

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Banditry and kidnapping are an organized crime committed by outlaws typically involving the threat or use of violence and unlawful abduction and confinement of a person against their will, it is a heinous crime posing a great security challenge to the democratic governance and peaceful coexistence of a community or country. This study aims to provide an overview of the geospatial hotspot mapping of banditry and kidnapping in Ussa and Takum local government areas of Taraba State with the objectives to map out banditry and kidnapping hotspot in the study area, to examine the spatial pattern of s

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L, Bilashini Chanu, Ngangbam Romeji, and Rajkumari Kajal. "Crime Pattern Analysis and Hot Spot Analysis in Bishnupur District of Manipur." International Journal of Science, Engineering and Management 9, no. 3 (2022): 12–16. http://dx.doi.org/10.36647/ijsem/09.03.a003.

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Manipur a northeastern state of India reported increasing crime rate as per NCRB records. Crime mapping using GIS environment in India is in budding stage and it is almost nil in the state of Manipur. Mapping different categories of crime/ criminal activity for pattern analysis and hotspot analysis is being done in the Bishnupur District of Manipur. There are alto-gather seven police stations in this district. Present study is dealing with spatial analysis of criminal activities for five years (2016–2020) using Spatial Statistics tool and hotspot analysis (Getis-ord Gi*). Mapping of crime loca

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Tang, Yicheng, Xinyan Zhu, Wei Guo, Ling Wu, and Yaxin Fan. "Anisotropic Diffusion for Improved Crime Prediction in Urban China." ISPRS International Journal of Geo-Information 8, no. 5 (2019): 234. http://dx.doi.org/10.3390/ijgi8050234.

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As a major social issue during urban development, crime is closely related to socioeconomic, geographic, and environmental factors. Traditional crime prediction models reveal the spatiotemporal dynamics of crime risks, but usually ignore the environmental context of the geographic areas where crimes occur. Therefore, it is difficult to enhance the spatial accuracy of crime prediction. We propose the use of anisotropic diffusion to include environmental factors of the evaluated geographic area in the traditional crime prediction model, thereby aiming to predict crime occurrence at a finer scale

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Komilova, Nilufar, Bakhodir Makhmudov, and Normurod Latipov. "Study of crimes in the city of Kokand using GIS technologies and sociological questionnaires." 59, no. 59 (December 1, 2023): 125–39. http://dx.doi.org/10.26565/2410-7360-2023-59-10.

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Formulation of the problem. It is known that the influence of the demographic, social and economic conditions of the region on criminal activity is significantly high. In this place, researching the types of crime characteristic of cities with different functions, and identifying hotspots where criminal activity has intensified within the city will further enrich the scientific and practical aspects of the geography of crime. The use of geographic information systems (hereinafter GIS) in the implementation of these tasks is an important issue on the agenda of the field today. Analysis of recen

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Harcharan, Singh. "EFFECT OF EXISTING LANDUSE ON CRIMEJALANDHAR COMMISSIONERATE (CITY-1)." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 6, no. 6 (2019): 49–64. https://doi.org/10.5281/zenodo.3246623.

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The study of crime analysis or criminology with existing land use in the specific area like as Jalandhar Commissioner ate with the help of GIS technology has vital role in the research of effect of physical environment and land use in crime. Up to now, mainly most of the periodically theories and researches are concentrated on the places, surrounding environment and existing built-up especially during crime studies and researches to find out the root causes of the occurrences of criminal activities in specific  crime hotspot areas. The crimes committed by the offenders are differently stu

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Hajela, Gaurav, Meenu Chawla, and Akhtar Rasool. "Crime hotspot prediction based on dynamic spatial analysis." ETRI Journal 43, no. 6 (2021): 1058–80. http://dx.doi.org/10.4218/etrij.2020-0220.

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Dr., John Motsamai Modise. "Violence Prevention, General Deterrence, Community Policing, and Problem-Oriented Policing are all Components of Hot Spot Policing." Violence Prevention, General Deterrence, Community Policing, and Problem-Oriented Policing are all Components of Hot Spot Policing 8, no. 4 (2023): 17. https://doi.org/10.5281/zenodo.10060289.

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This article seeks to assess the effectiveness of all hot spot policing components in lowering crime. A critical first step in enhancing public safety is the identification of criminal hotspot locations. Law enforcement agencies can gain from accurate and effective location identification by receiving information that can be used to lessen criminal activity. It would be more logical to utilize these resources in places with much higher crime rates given the limited resources at law enforcement's disposal. Police strategies that concentrate resources on smaller locations with high crime densiti

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Mustafa, Anith Nabilah, and Siti Rasidah Md Sakip. "HIGH-RAISED BUILDINGS IN URBAN AREA CONTRIBUTES TO THE SNATCH THEFT INCIDENTS." Malaysian Journal of Sustainable Environment 3, no. 2 (2017): 65. http://dx.doi.org/10.24191/myse.v3i2.5595.

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Snatch theft incidents are on the rise in Malaysia especially in the cities. It tends to happen in cities because there is a possibility to commit it and both crime and urban are often associated with each other. The aim of this paper is to find out whether the building with two or more levels in urban area contributes to the snatch theft incidents. The present study has been taken up to detect the hotspots of snatch theft in Selangor, Malaysia. The crime data were obtained by requesting and analysing the index crime statistical data from the Royal Malaysian Police (RMP). This study made use o

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Goodson, Heidi. "Examining the Modeling Framework of Crime Hotspot Models in Predictive Policing." Journal of Humanistic Mathematics 11, no. 2 (2021): 465–76. http://dx.doi.org/10.5642/jhummath.202102.28.

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Predictive policing has its roots in crime hotspot modeling. In this paper we give an example of what goes into mathematical crime hotspot modeling and show that the modeling assumptions perpetuate systemic racism in policing. The goal of this paper is to raise objections to this field of research, not on its mathematical merit, but on the scope of the problem formation. We do not make any suggestions about how to incorporate race into predictive policing models in order to make them less biased.

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