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- W2972314353 abstract "In recent years, death involving road accidents has become a global raising trend since more people are dependent on automobile transportation. Thus, this work was done to forecast road fatalities for years ahead in Malaysia using three different forecasting models with past data collected as comparison. Comparison between 3 types of forecasting model which were ARIMA(0,1,1), Poisson GLM and Negative Binomial GLM was done and the most suitable model following Malaysia's trend was determined. Road traffic fatality data was taken from Malaysian Institute of Road Safety Research. The data analysis was done by using R programming and EViews. The comparison was done in term of mean squared error, (MSE), root-mean-square error (RMSE), relative forecast error (RFE), mean absolute deviation (MAD) and mean absolute percentage error (MAPE). Results showed that ARIMA model is the best fitted model among Poisson and Negative Binomial models. Hence, the time series ARIMA model has been considered the best models compared to Poisson regression GLM model and Negative Binomial regression GLM model." @default.
- W2972314353 created "2019-09-19" @default.
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- W2972314353 date "2019-07-08" @default.
- W2972314353 modified "2023-10-09" @default.
- W2972314353 title "Fatality Involving Road Accidents in Malaysia" @default.
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- W2972314353 doi "https://doi.org/10.1145/3343485.3343494" @default.
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