Crime Forecasting and Analysis: A Machine Learning Perspective

Soumadip Saha , Aniket Hazra

Artificial Neural Networks, Crime Prediction, Machine Learning, Data Analysis, Law Enforcement

Predicting crime remains a major challenge for ensuring community safety, as traditional methods often fail to capture the complexities of modern urban environments. This research proposes a comprehensive machine learning and time series-based framework to enhance crime prediction capabilities. The study has three primary objectives: (1) to use supervised learning algorithms to predict crime types based on historical data, including features such as time, location, and previous crime patterns; (2) to apply spatial analysis techniques to identify and map high-risk crime zones using the Indian Crime Dataset; and (3) to forecast future crime trends through time series modeling, thereby supporting more effective resource allocation and strategic planning by law enforcement agencies. By integrating data-driven approaches, this research aims to improve the accuracy and reliability of crime forecasting models. The framework also evaluates the performance of different machine learning models to determine their suitability for large-scale urban crime analysis, with the ultimate goal of strengthening proactive crime prevention strategies and enhancing public safety outcomes.

Published Paper   E-Certificate

"Crime Forecasting and Analysis: A Machine Learning Perspective", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 5, page no.c908-c913, May-2025, Available :https://ijsdr.org/papers/IJSDR2505285.pdf

Volume 10 Issue 5, May-2025

Pages : c908-c913

Paper Reg. ID: IJSDR_302895

Published Paper Id: IJSDR2505285

Downloads: 000523

Research Area: Science and Technology

Country: Kolkata, West Bengal, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2505285

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2505285

DOI: https://doi.org/10.56975/ijsdr.v10i5.302895

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition