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A Multivariate Regression Model for Identifying, Analyzing and Predicting Crimes

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Abstract

Crime is canonically “capricious”. It is not necessarily hap-hazardous, but neither does it occur consistently. A better theoretical perception is needed to facilitate practical crime prevention solutions that correspond to specific places and times. Crime analysis and prevention is a systematic approach for identifying and analyzing patterns and trends in crime. Crime data analysts helps in law enforcement officers to speed up the process of solving crimes, owing to increase in the advent of computerized systems. This research is an attempt to forecast the occurrences of crimes, and predicts the frequency (count) of crimes at beat-day level in the city of Chicago. Forecasting crimes helps in taking care of crime prevention methods and the frequency of crimes helps to focus on the type of crime. This novel work is a collaboration between computer science and criminal justice aimed to develop a data mining procedure that can help solve crimes faster. Instead of focusing on causes of crime occurrence like political enmity, the criminal background of the offender etc. the author focused on crime factors for each day.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology (ISM), Dhanbad, Dhanbad, Jharkhand, 826004, India

    Siddharth Shukla, Praphula Kumar Jain & Rajendra Pamula

  2. Department of Computer Science and Engineering, Geethanjali College of Engineering and Technology, Cheeryal, Hyderabad, India

    Ch. Ramesh Babu

Authors
  1. Siddharth Shukla
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  2. Praphula Kumar Jain
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  3. Ch. Ramesh Babu
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  4. Rajendra Pamula
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Correspondence to Praphula Kumar Jain.

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Shukla, S., Jain, P.K., Babu, C.R. et al. A Multivariate Regression Model for Identifying, Analyzing and Predicting Crimes. Wireless Pers Commun 113, 2447–2461 (2020). https://doi.org/10.1007/s11277-020-07335-w

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  • DOI: https://doi.org/10.1007/s11277-020-07335-w

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