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Time Series Analysis for Crime Forecasting Using ARIMA (Autoregressive Integrated Moving Average) Model

Time Series Analysis for Crime Forecasting Using ARIMA (Autoregressive Integrated Moving Average) Model
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Author(s): Neetu Faujdar (Amity University, Noida, India) and Anant Joshi (Amity University, Noida, India)
Copyright: 2021
Pages: 41
Source title: Advancements in Security and Privacy Initiatives for Multimedia Images
Source Author(s)/Editor(s): Ashwani Kumar (Vardhaman College of Engineering, India) and Seelam Sai Satyanarayana Reddy (Vardhaman College of Engineering, India)
DOI: 10.4018/978-1-7998-2795-5.ch007

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Abstract

With massive advancements in the fields of data analysis and data mining, a new importance has been gained by data visualization. Data visualization focuses on visualizing and abstracting complex data to make it comprehensible and easy to understand using visual representation of information. Analysis of crime and crime-related data has been steadily popularizing over the last decade, and this chapter aims at visualizing such data. Crime data for several different types of crime for many countries in the world has been collected, compiled, processed, analyzed, and visualized in this chapter. Predictive analysis of this data has also been performed using time series analysis. This chapter aims to create a hub where internet users can easily view and interpret this data.

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