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Advanced Crime Prediction and Analysis Using Machine Learning and Quantum Networking
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Author(s): Jeremy Gideon J. (Sathyabama Institute of Science and Technology, India), J. Jefrin (Sathyabama Institute of Science and Technology, India)and S. Dhamodaran (Sathyabama Institute of Science and Technology, India)
Copyright: 2025
Pages: 14
Source title:
Multidisciplinary Applications of AI and Quantum Networking
Source Author(s)/Editor(s): Christo Ananth (Samarkand State University, Uzbekistan), Osamah Ibrahim Khalaf (Al-Nahrain University, Iraq)and Jose Anand (KCG College of Technology, India)
DOI: 10.4018/979-8-3693-9336-9.ch007
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Abstract
Researchers have recently focused a great deal of attention on the utilization of deep learning and machine learning methods to the prediction of crimes, with a focus on identifying trends and patterns in the incidence of crimes. This review investigates more than 150 publications to examine the numerous machine learning techniques that forecast crime. Availability of the utilized datasets by academics for predicting crimes is made possible by this study, which also examines popular methods for forecasting criminal activity using deep gaining knowledge of and machine learning algorithms. These methods provide insights into many patterns and variables associated with criminal activity. Lastly, scholars in this subject will find great use for the thorough summary of studies on deep learning and machine learning approaches to forecasting crime provided in this publication. Law enforcement organizations can create more effective plans to deter and address criminal activity by developing a greater understanding of crime prediction techniques.
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