Forecasting road deaths in Malaysia using support vector machine

Nurul Qastalani, Radzuan and Mohd Hasnun, Arif Hassan and Anwar P.P., Abdul Majeed and Rabiu Muazu, Musa and Khairil Anwar, Abu Kassim (2020) Forecasting road deaths in Malaysia using support vector machine. The 5th International Conference on Electrical, Control & Computer Engineering (InECCE 2019). ISSN ISBN:978-981-15-2317-5. (In Press / Online First) (In Press / Online First)

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Abstract

An average of 6,350 people died every year in Malaysia due to road traffic accidents. A published data of Malaysian road deaths in 20 years since 1997 reveals that the number of fatalities has not really declined with a difference of less than 10% from one year to the next. Forecasting the number of fatalities is beneficial in planning a counter measure to bring down the death toll. A predictive model of Malaysian road death has been developed using a time-series model known as auto regressive integrated moving average (ARIMA). The model was used in the previous Road Safety Plan of Malaysia to set a target death toll to be reduced in 2020, albeit being inaccurate. This study proposes a new approach in forecasting the road deaths, by means of a machine learning algorithm known as Support Vector Machine. The length of various types of road, number of registered vehicles and population were among the eight features used to develop the model. Comparison between the actual road deaths and the prediction demonstrates a good agreement, with a mean absolute percentage error of 2% and an R-squared value of 85%. The Linear kernel-based Support Vector Machine was found to be able to predict the road deaths in Malaysia with reasonable accuracy. The developed model could be used by relevant stakeholders in devising appropriate poli-cies and regulations to reduce road fatalities in Malaysia.

Item Type: Article
Uncontrolled Keywords: Forecasting road deaths; Malaysia; support vector machine; The Linear kernel-based
Subjects: T Technology > TD Environmental technology. Sanitary engineering
Faculty/Division: Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User: Miss. Ratna Wilis Haryati Mustapa
Date Deposited: 31 Jan 2020 09:03
Last Modified: 31 Jan 2020 09:03
URI: http://umpir.ump.edu.my/id/eprint/27603
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