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A Latest Approach for Crime Rate Prediction and Analysis by Using the Clustering and Machine Learning Algorithm

A. Ananda Kumar, K. Ramanan, M. Santhosh Prakash, P. M. Sivaraja


In our daily life, the collection and analysis of crime-related data is uncertain from a security perspective. Crime rate forecasting and analysis is a way of identifying and analyzing crime patterns in crime data contained in a crime database. Our system predicts what criminal activity occurs in everyday life in various parts of the world. Through the utilization of machine learning and data mining algorithms, it is possible to forecast the details present within the dataset. This process helps solve the crime faster. Instead of focusing on why the crime happened, background locations are also provided. We use K-means clustering algorithm and linear regression algorithm to improve criminology. It allows analysis of crime data based on monthly and weekly data.


Crime rate prediction, machine learning, data mining, k-means, clustering, linear regression

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Yadav S, Timbadia M, Yadav A, Vishwakarma R, Yadav N. Crime pattern detection, analysis & prediction. In 2017 IEEE International conference of Electronics, Communication and Aerospace Technology (ICECA). 2017 Apr 20; 1: 225–230.

Sivaranjani S, Sivakumari S, Aasha M. Crime prediction and forecasting in Tamil Nadu using clustering approaches. In 2016 IEEE International Conference on Emerging Technological Trends (ICETT). 2016 Oct 21; 1–6.

Sharma M, Z-CRIME: A data mining tool for the detection of suspicious criminal activity based on decision tree. 2014 International Conference on Data Mining and Intelligent Computing (ICDMIC), Delhi, India, 2014. p. 1-6. doi: 10.1109/ICDMIC.2014.6954268.

Thongsatapornwatana U. A survey of data mining techniques for analyzing crime patterns. In 2016 IEEE 2nd Asian Conference on Defence Technology (ACDT). 2016 Jan 21; 123–128.

Hussain KZ, Durairaj M, Farzana GR. Application of data mining techniques for analyzing violent criminal behavior by simulation model. International Journal of Computer Science and Information Technology & Society (IJCSITS). 2012; 2(01): 25–29.

Azeez J, Aravindhar DJ. Hybrid approach to crime prediction using deep learning. In 2015 IEEE International Conference on Advances in Computing, Communications and Informatics (ICACCI). 2015 Aug 10; 1701–1710.

Dubey N, Chaturvedi SK. A survey paper on crime prediction technique using data mining. Int J Eng Res Appl. 2014;4(3):396–400.

Lin Y, Chen T, Yu L. Using machine learning to assist crime prevention. In 2017 IEEE 6th IIAI International Congress on Advanced Applied Science (IIAI-AAI). 2017; 1029–1030.

Marchant R, Haan S, Clancey G, Cripps S. Applying machine learning to criminology: semi parametric spatial demographic Bayesian regression. Secur Inform. 2018; 7(1): 1.

Manish Gupta, Chandra B, Gupta MP. Crime Data Mining for Police Information System. IIT Delhi; 2017.


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