STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal Of Network security

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

  1. A. Ananda Kumar
  2. K. Ramanan
  3. M. Santhosh Prakash
  4. P. M. Sivaraja

Abstract

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.

Keywords

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