Relevant bibliographies by topics / Crime forecasting

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Crime forecasting'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Crime forecasting"

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Tariq, Haseeb, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Sabeen Bari, Muhammad Shahzad Sarfraz, and Rozita Jamili Oskouei. "Employing Deep Learning and Time Series Analysis to Tackle the Accuracy and Robustness of the Forecasting Problem." Security and Communication Networks 2021 (March 31, 2021): 1–10. http://dx.doi.org/10.1155/2021/5587511.

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Crime is a bone of contention that can create a societal disturbance. Crime forecasting using time series is an efficient statistical tool for predicting rates of crime in many countries around the world. Crime data can be useful to determine the efficacy of crime prevention steps and the safety of cities and societies. However, it is a difficult task to predict the crime accurately because the number of crimes is increasing day by day. The objective of this study is to apply time series to predict the crime rate to facilitate practical crime prevention solutions. Machine learning can play an
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Abdurasulova, Kumrinisa, and Raziya Buranova. "CRIME FORECASTING AND METHODS OF IMPLEMENTATION." Review of Law Sciences 7, no. 3 (2023): 76–87. http://dx.doi.org/10.51788/tsul.rols.2023.7.3./tamw8465.

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The article reveals the history of the development of forecasting, the concept of forecasting, scientific forecasting, the importance of forecasting in criminology, including other sciences, the essence, features, and differentiation of criminological forecasting, its tasks, goals, and types, which include crime in general, but also the concept of forecasting individual criminal behavior, criminological situations, subjects and objects of forecasting, and their role in choosing the method to be used for forecasting crime. The general and special methods of realization of crime forecasting are
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Khairuddin, Alif Ridzuan, Razana Alwee, and Habibollah Harun. "Comparative Study on Artificial Intelligence Techniques in Crime Forecasting." Applied Mechanics and Materials 892 (June 2019): 94–100. http://dx.doi.org/10.4028/www.scientific.net/amm.892.94.

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An application of efficient crime analysis is beneficial and helpful to understand the behavior of trend and pattern of crimes. Crime forecasting is an area of research that assists authorities in enforcing early crime prevention measures. Statistical technique has been widely applied in the past to develop crime forecasting models. However, it has been observed that researchers have begun to shift their research interests from statistical model to artificial intelligence model in crime forecasting. Thus, this study is conducted to observe the capabilities of artificial intelligence technique
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Stupar, Davor. "Criminal intelligence as a prerequisite for quality crime forecasting." Zurnal za bezbjednost i kriminalistiku 3, no. 2 (2021): 57–74. http://dx.doi.org/10.5937/zurbezkrim2101057s.

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Crime forecasting in studying new and adapting one's own methods, and as a part of criminalistic strategy in combating crime as a preliminary stage, must gain a wider knowledge of the same. For any crime forecasting, it is necessary to have crime data, which are systematically processed in their form and structure and stored in records and databases, while data collection is an essential part on which criminal intelligence activity is based. Criminal intelligence activity precedes criminal intelligence analysis, which can be defined as a system in the process of collecting, processing and pres
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Mohamad Zamri, Nurul Farhana, Nooritawati Md Tahir, Megat Syahirul Amin Megat Ali1, Nur Dalila Khirul Ashar, and Ali Abd Al-misreb. "Mini-review of Street Crime Prediction and Classification Methods." Jurnal Kejuruteraan 33, no. 3 (2021): 391–401. http://dx.doi.org/10.17576/jkukm-2021-33(3)-02.

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Crime rates are one of the biggest problems in today’s modern society, especially in urban cities. Various techniques on crime prediction and detection have been developed by previous researchers in reducing the crime rates that keep increasing throughout the year as well as to assist the government authorities in combating crimes. These include studies on forecasting crime activities based on both primary and secondary data that include numerical data, statistics, video, and images related to various categories of crimes. Thus, in this study, a mini-review is conducted related to the database
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Singh, Rohit. "Crime Forecasting in India." International Scientific Journal of Engineering and Management 04, no. 04 (2025): 1–7. https://doi.org/10.55041/isjem02917.

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Since British rule, India has kept track of crime. Today, the Home Affairs Ministry directs the National Crime Records Bureau to compile annual statistics. Crime rates are rising as the country develops and grows, necessitating analysis. The goal of this study is to identify trends in crime over time in order to forecast future developments and improve the nation's crime rate. To identify trends in crime records, the study employs a variety of exploratory techniques. Additionally, it displays data with its various features and attempts to predict future trends using machine learning. The goal
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Lee, YongJei, and SooHyun O. "Flag and boost theories for hot spot forecasting: An application of NIJ’s Real-Time Crime forecasting algorithm using Colorado Springs crime data." International Journal of Police Science & Management 22, no. 1 (2019): 4–15. http://dx.doi.org/10.1177/1461355719864367.

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By operationalizing two theoretical frameworks, we forecast crime hot spots in Colorado Springs. First, we use a population heterogeneity (flag) framework to find places where the hot spot forecasting is consistently successful over months. Second, we use a state dependence (boost) framework of the number of crimes in the periods prior to the forecasted month. This algorithm is implemented in Microsoft Excel®, making it simple to apply and completely transparent. Results shows high accuracy and high efficiency in hot spot forecasting, even if the data set and the type of crime we used in this
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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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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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Dissertations / Theses on the topic "Crime forecasting"

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Chukwu, Idam Oko. "Public expenditures and crime in a free society." CSUSB ScholarWorks, 1999. https://scholarworks.lib.csusb.edu/etd-project/1802.

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Cohn, Ellen Gail. "The effects of weather and temporal variables on calls for police service." Thesis, University of Cambridge, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386413.

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Breetzke, Gregory Dennis. "Geo-analysis of offenders in Tshwane: towards an urban ecological theory of crime in South Africa /." Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-01062009-141141/.

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Alshalan, Abdullah. "Cyber-crime fear and victimization." Diss., Mississippi State : Mississippi State University, 2006. http://library.msstate.edu/etd/show.asp?etd=etd-01232006-095728.

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Воскобойнік, І. І. "Статистичний аналіз та прогнозування рівня злочинності в Україні". Thesis, Одеський національний економічний університет, 2020. http://dspace.oneu.edu.ua/jspui/handle/123456789/12542.

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У роботі розглядаються теоретичні та методологічні питання щодо статистичної оцінки правопорушень та злочинності в Україні. Проаналізовано динаміку рівня злочинності в Україні та проаналізована структура злочинів. Проведено аналіз регіональних особливостей розповсюдженості злочинності в Україні. Проведено аналіз тенденції розвитку та рівня злочинності в Україні.<br>The paper considers theoretical and methodological issues related to statistical assessment of offenses and crime in Ukraine. The dynamics of the crime rate in Ukraine is analyzed and the structure of crimes is analyzed. The analy
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Holm, Noah, and Emil Plynning. "Spatio-temporal prediction of residential burglaries using convolutional LSTM neural networks." Thesis, KTH, Geoinformatik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229952.

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The low amount solved residential burglary crimes calls for new and innovative methods in the prevention and investigation of the cases. There were 22 600 reported residential burglaries in Sweden 2017 but only four to five percent of these will ever be solved. There are many initiatives in both Sweden and abroad for decreasing the amount of occurring residential burglaries and one of the areas that are being tested is the use of prediction methods for more efficient preventive actions. This thesis is an investigation of a potential method of prediction by using neural networks to identify are
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Cicconi, Claudia. "Essays on macroeconometrics and short-term forecasting." Doctoral thesis, Universite Libre de Bruxelles, 2012. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209660.

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The thesis, entitled "Essays on macroeconometrics and short-term forecasting",<p>is composed of three chapters. The first two chapters are on nowcasting,<p>a topic that has received an increasing attention both among practitioners and<p>the academics especially in conjunction and in the aftermath of the 2008-2009<p>economic crisis. At the heart of the two chapters is the idea of exploiting the<p>information from data published at a higher frequency for obtaining early estimates<p>of the macroeconomic variable of interest. The models used to compute<p>the nowcasts are dynamic models conceived f
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Barbosa, Guilherme Valentim. "Análise de bolhas imobiliárias ao redor do mundo." reponame:Repositório Institucional do FGV, 2018. http://hdl.handle.net/10438/24764.

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Submitted by Guilherme Valentim Barbosa (guilhermevalentim@gmail.com) on 2018-09-18T02:06:09Z No. of bitstreams: 1 Guilherme Valentim Barbosa - Dissertação - 20180917.pdf: 947230 bytes, checksum: a6fd42e0aefd410304cfa0f0ba723d7b (MD5)<br>Approved for entry into archive by Joana Martorini (joana.martorini@fgv.br) on 2018-09-18T14:55:42Z (GMT) No. of bitstreams: 1 Guilherme Valentim Barbosa - Dissertação - 20180917.pdf: 947230 bytes, checksum: a6fd42e0aefd410304cfa0f0ba723d7b (MD5)<br>Approved for entry into archive by Suzane Guimarães (suzane.guimaraes@fgv.br) on 2018-09-19T13:06:39Z (GMT) N
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Singh, Prakash. "Time series forecasting on crime data in Amsterdam for a software company." Master's thesis, 2018. http://hdl.handle.net/10362/57826.

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Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics<br>In recent years, there have been many discussions of data mining technology implementation in the fight against terrorism and crime. Sentient as a software company has been supporting the police for years by applying data mining techniques in the DataDetective application (Sentient, 2017). Experimenting with various types of predictive model solutions, selecting the most efficient and promising solution are the objectives of this internship. Initially, extended lite
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Miles, Thomas John. "Three empirical essays in the economics of crime /." 2000. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:9965120.

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Books on the topic "Crime forecasting"

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English, Kim. Measuring crime rates of prisoners. Colorado Dept. of Public Safety, Division of Criminal Justice, Office of Research and Statistics, 1992.

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Babachinaitė, G. Nusikalstamumas Lietuvoje ir jo prognozė iki 2015 m.: Monografija. Mykolo Romerio universiteto Leidybos centras, 2008.

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Vserossiĭskiĭ nauchno-issledovatelʹskiĭ institut (Russia (Federation). Ministerstvo vnutrennikh del), ed. Sostoi͡a︡nie prestupnosti v Rossiĭskoĭ Federat͡s︡ii i ee dolgosrochnyĭ prognoz. Ministerstvo vnutrennikh del Rossiĭskoĭ Federat͡s︡ii. Vserossiĭskiĭ nauchno-issl. institut, 1998., 1998.

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Chalka, Robert. Prognóza vývoja kriminality v Slovenskej republike. Akadémia policajného zboru v Bratislave, 2000.

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Beken, T. vander. European organised crime scenarios for 2015. Maklu, 2006.

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Deadman, Derek. Forecasting recorded property crime using a time-series econometric model. Public Sector Economics Research Centre, 1995.

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Weitemeier, Ingmar, and Rainer Dinkel. Demografie und Kriminalität: Eine Prognose zur Kriminalitätsentwicklung in Mecklenburg-Vorpommern. Verlag für Polizeiwissenschaft, 2008.

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Muraskin, Roslyn. Visions for change: Crime and justice in the twenty-first century. 4th ed. Prentice Hall, 2005.

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Babaev, Mikhail Matveevich, and V. A. Kikotʹ. Kriminogennai︠a︡ situat︠s︡ii︠a︡ v Rossiĭskoĭ Federat︠s︡ii v nachale XXI veka. VNII MVD RF, 2001.

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Gurov, A. I. Kriminogennai︠a︡ situat︠s︡ii︠a︡ v Rossii na rubezhe XXI veka. OOO "I︠U︡risprudent︠s︡ii︠a︡", 2000.

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Book chapters on the topic "Crime forecasting"

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Gottschalk, Petter. "Forecasting Crime Occurrence." In Trusted White-Collar Offenders. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73862-4_10.

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Caffaro, Fabio, Lorenzo Bongiovanni, and Claudio Rossi. "Geo-temporal Crime Forecasting Using a Deep Learning Attention-Based Model." In Security Informatics and Law Enforcement. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-62083-6_26.

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AbstractCrime prediction is a crucial problem in law enforcement, and the ability to forecast where and when crimes are likely to occur can help police departments allocate their resources effectively and prevent crimes. In this chapter, we propose a geo-temporal crime forecasting model based on a transformer architecture. We use a public dataset from the Boston Police Department and forecast crimes in each cell of a 1 km × 1 km grid. We use an encoder–decoder structure to capture the spatiotemporal patterns of the crimes. The encoder elaborates the crimes that occurred in each cell during the
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Johnson, Shane D., and Kate J. Bowers. "Near Repeats and Crime Forecasting." In Encyclopedia of Criminology and Criminal Justice. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-5690-2_210.

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Fox, James Alan. "Crime Forecasting and the Disappearing Juvenile Crime Wave." In The Routledge International Handbook of Juvenile Homicide. Routledge, 2023. http://dx.doi.org/10.4324/9781003242833-2.

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Faujdar, Neetu, Yashita Verma, Yogesh Singh Rathore, and P. K. Rohatgi. "Crime Forecasting Using Time Series Analysis." In Advances in Interdisciplinary Research in Engineering and Business Management. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0037-1_20.

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Mu, Yang, Wei Ding, Melissa Morabito, and Dacheng Tao. "Empirical Discriminative Tensor Analysis for Crime Forecasting." In Knowledge Science, Engineering and Management. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25975-3_26.

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Sharma, Shivani, Bipin Kumar Rai, Gautam Kumar, Aakash Prajapati, and Vaibhav Kumar. "Crime Visualization and Forecasting Using Machine Learning." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2058-7_28.

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Beken, Tom Vander. "Risk, Uncertainty and the Assessment of Organised Crime." In Forecasting, Warning and Responding to Transnational Risks. Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230316911_6.

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Devi, J. Vimala, and K. S. Kavitha. "Time Series Analysis and Forecasting on Crime Data." In Algorithms for Intelligent Systems. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6332-1_26.

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Yu, Chung-Hsien, Wei Ding, Ping Chen, and Melissa Morabito. "Crime Forecasting Using Spatio-temporal Pattern with Ensemble Learning." In Advances in Knowledge Discovery and Data Mining. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06605-9_15.

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Conference papers on the topic "Crime forecasting"

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Wijethunge, Tinaya, Sampath Edirisinghe, Mansik Jeon, Jeehyun Kim, Ruchire Wijesinghe, and Bhagya Silva. "Towards Holistic Crime Management Through Descriptive Analysis and Predictive Forecasting." In 2024 6th International Conference on Advancements in Computing (ICAC). IEEE, 2024. https://doi.org/10.1109/icac64487.2024.10850920.

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Khatod, Swadha, Vedanti Shukla, and Ayesha Hakim. "Harnessing Machine Learning and Computer Vision Strategies for Crime Forecasting." In 2025 1st International Conference on AIML-Applications for Engineering & Technology (ICAET). IEEE, 2025. https://doi.org/10.1109/icaet63349.2025.10932290.

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Dubey, Aditya, Nookala Venu, Dhananjay Bisen, Priyanka Garg, Kande Srinivas, and Hemlata Arya. "A Clustering-Based Method for Hotspot Recognition in Crime Forecasting." In 2024 IEEE 8th International Conference on Information and Communication Technology (CICT). IEEE, 2024. https://doi.org/10.1109/cict64037.2024.10899713.

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Rani, Reenu, Rohan Mehta, Sabeeh Israr, Umar Tamboli, Rohith M, and Sanvi Chavan. "A Synergistic Ensemble Approach for Enhanced Time Series Forecasting in Crime Analytics." In 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit). IEEE, 2024. https://doi.org/10.1109/globalaisummit62156.2024.10947957.

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Arifman, Firman, Nanan Soekarna, Teddy Mantoro, and Media Anugerah Ayu. "Crime Time-Series Forecasting in Indonesia Using Neural Network and Linear Regression." In 2024 10th International Conference on Computing, Engineering and Design (ICCED). IEEE, 2024. https://doi.org/10.1109/icced64257.2024.10983366.

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Nauzad, Hamza, Dhanuka Dayawansa, Nethya Yavindi Dias, Prasanna S. Haddela, and Samadhi Ratnayake. "Predictive Policing with Neural Networks: A Big Data Approach to Crime Forecasting in Sri Lanka." In 2025 International Research Conference on Smart Computing and Systems Engineering (SCSE). IEEE, 2025. https://doi.org/10.1109/scse65633.2025.11031003.

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Megalathan, Gajaanuja, and Banuka Athuraliya. "“CrimeLock” A Mobile Application for Analysing and Forecasting Crime using Autoregressive Integrated Moving Average with Artificial Neural Network." In 2024 Intelligent Systems and Machine Learning Conference (ISML). IEEE, 2024. https://doi.org/10.1109/isml60050.2024.11007295.

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R, Anuvarshini S., Deeksha Nidhi, Deeksha Sree C, and Krishna Sowjanya K. "Crime Forecasting : A Theoretical Approach." In 2022 IEEE 7th International Conference on Recent Advances and Innovations in Engineering (ICRAIE). IEEE, 2022. http://dx.doi.org/10.1109/icraie56454.2022.10054345.

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Borowik, Grzegorz, Zbigniew M. Wawrzyniak, and Pawel Cichosz. "Time series analysis for crime forecasting." In 2018 26th International Conference on Systems Engineering (ICSEng). IEEE, 2018. http://dx.doi.org/10.1109/icseng.2018.8638179.

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Yu, Chung-Hsien, Max W. Ward, Melissa Morabito, and Wei Ding. "Crime Forecasting Using Data Mining Techniques." In 2011 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2011. http://dx.doi.org/10.1109/icdmw.2011.56.

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