Crime Rate Prediction Using Time Series Forecasting

Madhu, Vishwakh (2023) Crime Rate Prediction Using Time Series Forecasting. Masters thesis, Dublin, National College of Ireland.

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Abstract

One of the most significant social issues in the nation is crime, which has an impact on socioeconomic position, child development, and public safety. In order to decrease crime and improve the quality of life for individuals, officials must have a clear understanding of the variables that contribute to increased crime. In our study, we address a basic issue: our research has undertaken a comparison method to estimate crime rates using the real-world crime data-set of the years 2007 to 2022 acquired from the official statistics web-site of the government. Whereas methods for estimating crime rates using time series data include SARIMA, Random Forest, XG Boost, and Prophet.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Rifai, Hicham UNSPECIFIED
Subjects:	H Social Sciences > HV Social pathology. Social and public welfare > Criminology > Crimes and Offences Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Tamara Malone
Date Deposited:	19 May 2023 15:50
Last Modified:	19 May 2023 15:50
URI:	https://norma.ncirl.ie/id/eprint/6609

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