Potential application of Artificial Neural Network (ANN) analysis method on Malaysian road crash data
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 transp...
| Auteurs principaux: | , , , , , , |
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| Format: | Article |
| Langue: | English |
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Penerbit UMP
2021
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| Sujets: | |
| Accès en ligne: | http://umpir.ump.edu.my/id/eprint/33556/1/Potential%20application%20of%20artificial%20neural%20network.pdf |
| _version_ | 1825814229754576896 |
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| author | Ahmad Noor Syukri, Zainal Abidin Ahmad Shahir, Jamaludin Mohd Nizar, Mhd Razali Azzuhana, Roslan Roziana, Shahril Zulhaidi, Mohd Jawi Khairil Anwar, Abu Kassim |
| author_facet | Ahmad Noor Syukri, Zainal Abidin Ahmad Shahir, Jamaludin Mohd Nizar, Mhd Razali Azzuhana, Roslan Roziana, Shahril Zulhaidi, Mohd Jawi Khairil Anwar, Abu Kassim |
| author_sort | Ahmad Noor Syukri, Zainal Abidin |
| collection | UMP |
| description | 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. |
| first_indexed | 2024-03-06T12:55:42Z |
| format | Article |
| id | UMPir33556 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:55:42Z |
| publishDate | 2021 |
| publisher | Penerbit UMP |
| record_format | dspace |
| spelling | UMPir335562022-03-22T05:03:45Z http://umpir.ump.edu.my/id/eprint/33556/ Potential application of Artificial Neural Network (ANN) analysis method on Malaysian road crash data Ahmad Noor Syukri, Zainal Abidin Ahmad Shahir, Jamaludin Mohd Nizar, Mhd Razali Azzuhana, Roslan Roziana, Shahril Zulhaidi, Mohd Jawi Khairil Anwar, Abu Kassim TA Engineering (General). Civil engineering (General) TS Manufactures 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. Penerbit UMP 2021-08 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/33556/1/Potential%20application%20of%20artificial%20neural%20network.pdf 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) https://doi.org/10.15282/jmmst.v5i2.6706 https://doi.org/10.15282/jmmst.v5i2.6706 |
| spellingShingle | TA Engineering (General). Civil engineering (General) TS Manufactures Ahmad Noor Syukri, Zainal Abidin Ahmad Shahir, Jamaludin Mohd Nizar, Mhd Razali Azzuhana, Roslan Roziana, Shahril Zulhaidi, Mohd Jawi Khairil Anwar, Abu Kassim Potential application of Artificial Neural Network (ANN) analysis method on Malaysian road crash data |
| title | Potential application of Artificial Neural Network (ANN) analysis method on Malaysian road crash data |
| title_full | Potential application of Artificial Neural Network (ANN) analysis method on Malaysian road crash data |
| title_fullStr | Potential application of Artificial Neural Network (ANN) analysis method on Malaysian road crash data |
| title_full_unstemmed | Potential application of Artificial Neural Network (ANN) analysis method on Malaysian road crash data |
| title_short | Potential application of Artificial Neural Network (ANN) analysis method on Malaysian road crash data |
| title_sort | potential application of artificial neural network ann analysis method on malaysian road crash data |
| topic | TA Engineering (General). Civil engineering (General) TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/33556/1/Potential%20application%20of%20artificial%20neural%20network.pdf |
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