학술논문

An Approach on Cyber Crime Prediction Using Prophet Time Series
Document Type
Conference
Source
2022 IEEE 7th International conference for Convergence in Technology (I2CT) Convergence in Technology (I2CT), 2022 IEEE 7th International conference for. :1-5 Apr, 2022
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Law enforcement
Shape
Time series analysis
Government
Predictive models
Market research
Data models
Time series Analysis
Prophet Model
Fourier series
Crime Prediction
Language
Abstract
The advancement of technology in every facet of human existence has moulded a far broader crime-solving strategy. Extensive medical study has been conducted on the origins and shape of crime, as well as its intensity and dynamics, with the help of researchers from several scientific disciplines. Government agencies and police departments now have more options for tracking crime events, including the capacity to gather and preserve specific data as well as spatial and temporal information. Prophet is an additive model-based approach for forecasting time series data that matches non-linear patterns with yearly, weekly, and daily seasonality, as well as the holiday effect. It employs a decomposable model that consists of three primary components: trend, seasonality, and holiday effects. The Prophet model is used in this paper to predict crimes.