JT Lalis
Researcher
Accident Forecasting is to forecast the safety state based on the available information and observation.
The dataset being used in this app is UKDriverDeaths. It is a time series dataset giving the monthly totals of car drivers in Great Britain killed or seriously injured Jan 1969 to Dec 1984. Compulsory wearing of seat belts was introduced on 31 Jan 1983.
This Shiny app is designed to provide a lightweight yet accurate way of forecasting accidents to help decision making and planning before casualty and loss occur.
The Naive forecasting method was used to develop this Shiny app. For more information about the method, follow the link below:
To start using the Shiny App, click the link below:
https://skycrater.shinyapps.io/DDP_Project/
The sample line graph can be seen below:
## Loading required package: reshape2
## Warning: package 'reshape2' was built under R version 3.2.5
The performance of the forecasting method being used in this Shiny App was measured using symmetric mean absolute percentage error (SMAPE).
For more details about SMAPE, click the link below: https://en.wikipedia.org/wiki/Symmetric_mean_absolute_percentage_error
Thank you.