An Approach on Cyber Crime Prediction Using Prophet Time Series
Aakriti Nag, Rohit Ranjan, C. N. S. Vinoth Kumar · 2022 IEEE 7th International conference for Convergence in Technology (I2CT) · 2022
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.