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| Main Authors: | , |
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| Format: | Recurso digital |
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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.19380432 |
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Table of Contents:
- <p><a href="https://ijetrm.com/issues/files/Apr-2026-02-1775100130-CRIME-APR2026-04.pdf" target="_blank" rel="noopener"><em><strong>Crime is one of the major concerns f</strong></em></a>or society and government agencies as it affects public safety and social<br>stability. With rapid urbanization and population growth, crime patterns are becoming more complex, making<br>traditional analysis methods less effective. To overcome this, Machine Learning (ML) combined with data<br>visualization provides a better way to analyze crime data and identify hidden patterns.<br>This project focuses on developing a Crime Rate Analysis and Visualization System that uses ML algorithms to<br>analyze historical crime data, detect trends, and predict crime-prone areas. It also includes interactive dashboards<br>that help law enforcement and policymakers easily understand crime distribution. The system improves decisionmaking, supports efficient resource allocation, and helps in preventing crimes using data-driven insights</p>