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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: March 2024

Volume 9 | Issue 3

Impact factor: 8.15

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Paper Title: Crime Data Visualization and Forecasting Using SARIMA Algorithm
Authors Name: Safiya Mohd , Hithasri Muthyala
Unique Id: IJSDR2304134
Published In: Volume 8 Issue 4, April-2023
Abstract: Machine learning is the ability to perform specific tasks by using past experience data while measuring the performance, upgrading knowledge and skills by a system for developing the software application. SARIMA (Seasonal Auto regressive Integrated Moving Average) algorithm is a technique to forecast and predicts the approaching data. SARIMA contains seasonal and trend modules in which, it can support a univariate of seasonal module. The year wise crime data set is used to implement and visualize the crime rate in each district from each state. To visualize and analyze the crime data with the help of graphical representation of time series graphs as heat map, trend line and column charts. Crime data is mainly used to reduce the crime rate and predicting the different crimes in a particular location. It is used for police departments, law and social control agencies to analyze the past crime incident data and to reduce the crime activities in the country. The crime data analysis is used for government agencies to speed up the process of finding the incidents in the society and speedup the process with help of time series algorithms. SARIMA model gives better efficiency to predict the crime data to solve problems in easiest way and to reduce the crime rate in the country.
Keywords: Visualization, Forecasting, Prediction, SARIMA, ARIMA, Prophet.
Cite Article: "Crime Data Visualization and Forecasting Using SARIMA Algorithm", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.757 - 772, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304134.pdf
Downloads: 000336256
Publication Details: Published Paper ID: IJSDR2304134
Registration ID:205197
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 757 - 772
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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