2020
DOI: 10.1007/978-981-15-2317-5_22
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Forecasting Road Deaths in Malaysia Using Support Vector Machine

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Cited by 5 publications
(2 citation statements)
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“…Statistical analysis has been used to predict future road traffic accidents, with the aim to halve its number in accordance with the sustainable development goal (SDG) 3.6 [3]- [5]. More recently, machine learning algorithms, such as Artificial Neural Networks and Support Vector Machines, have been used in many sectors to predict the outcome of an action [6]- [10], including road traffic accidents [11]- [13].…”
Section: Introductionmentioning
confidence: 99%
“…Statistical analysis has been used to predict future road traffic accidents, with the aim to halve its number in accordance with the sustainable development goal (SDG) 3.6 [3]- [5]. More recently, machine learning algorithms, such as Artificial Neural Networks and Support Vector Machines, have been used in many sectors to predict the outcome of an action [6]- [10], including road traffic accidents [11]- [13].…”
Section: Introductionmentioning
confidence: 99%
“…Although the rate has slightly reduced by about 0.9 % from 2017, it is still a problem that warrants attention from the government and policymakers. Malaysia has recorded a yearly average of 6,350 fatalities due to road traffic accidents each year (Radzuan et al, 2019). The average value has not been changed much for the past 20 years, with a yearly difference of less than 10 %.…”
Section: Introductionmentioning
confidence: 99%