Ahmad Noor Syukri, Zainal Abidin and Ahmad Shahir, Jamaludin and Mohd Nizar, Mhd Razali and Azzuhana, Roslan and Roziana, Shahril and Zulhaidi, Mohd Jawi and Khairil Anwar, Abu Kassim (2021) Potential application of Artificial Neural Network (ANN) analysis method on Malaysian road crash data. Journal of Modern Manufacturing Systems and Technology (JMMST), 5 (2). pp. 95-105. ISSN 2636-9575. (Published)
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Abstract
By allowing the movement of commodities and people, road transportation benefits both nations and people. This provides improved access to work opportunities, educational attainment, recreation, and healthcare, all of which have a direct and indirect influence on people. The influence on road transportation, on the other hand, has a detrimental impact on people's health. When addressing road traffic accidents, it is common known that it has merely become a global pandemic, with over a million people dying on the road each year. Malaysia, as a growing country, has identified road safety as a major issue that must be addressed. Reliable road safety statistics are critical for comprehending, assessing, and monitoring the nature and scope of the road safety problem and its solutions, for setting ambitious but realistic safety targets, for designing and implementing effective road safety policies, and for monitoring their success. Several approaches are presently utilized by road safety researchers to produce road safety indicators. In Malaysia, nearly all decisions made by the country's higher authorities to enhance road safety are based on data supplied by relevant stakeholders. As a result, having the proper application of analysis as well as the trustworthiness of the data itself is critical. This article will give a review of the possible use of the Artificial Neural Network (ANN) Analysis technique on traffic road collision data and what it may provide to assist monitor or forecast road safety issues, specifically in Malaysia. A new era in the field of road accident investigation is being ushered in by the development and application of analytical methodologies, which are creating previously unimaginable situations. Due to the convergence of recent advancements in accident research models and the availability of potentially new sources of traffic data, this paradigm shift has been made possible. The study of road crashes has benefited significantly from the development of more advanced data processing methodologies and frameworks, thus the researchers will able to extract significant conclusions from the study of traffic data thanks to the application of these approaches.
| Item Type: | Article |
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| Uncontrolled Keywords: | Artificial Neural Network (ANN); Malaysia; Road crash data; Road safety; Accident investigation |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TS Manufactures |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Manufacturing and Mechatronic Engineering Technology |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 22 Mar 2022 05:03 |
| Last Modified: | 22 Mar 2022 05:03 |
| URI: | http://umpir.ump.edu.my/id/eprint/33556 |
| Download Statistic: | View Download Statistics |
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