Volume 5, Issue 2, June 2020, Page: 41-48
Determination of the Severity of Motorcycle and Tricycle Accidents in Nigeria
Terungwa Simon Yange, Department of Mathematics/Statistics/Computer Science, University of Agriculture, Makurdi, Nigeria
Oluoha Onyekwere, Department of Computer Science, University of Nigeria, Nsukka, Nigeria
Malik Adeiza Rufai, Department of Computer Science, Federal University, Lokoja, Lokoja, Nigeria
Charity Ojochogwu Egbunu, Department of Mathematics/Statistics/Computer Science, University of Agriculture, Makurdi, Nigeria
Onyinyechukwu Rehoboth Ogboli, Department of Computer Science, Federal University, Lokoja, Lokoja, Nigeria
Received: May 11, 2020;       Accepted: May 27, 2020;       Published: Jun. 17, 2020
DOI: 10.11648/j.aas.20200502.14      View  101      Downloads  14
Road traffic accidents are a very rampant issue causing injury, loss of lives and property worldwide. In this research, a system for determining the severity of motorcycle accidents in Lokoja Metropolis of Central Nigeria was developed. The research considered different areas that are highly prone to accidents in Lokoja. Although accidents cannot be totally avoided, through scientific analysis, their frequency and severity can be reduced. The methodology used in this research is Knowledge Discovery in Databases with the Decision Tree Algorithm as the soft computing technique used for analysis. Python programming language was used for the implementation. The dataset used was gotten from the Federal Road Safety Corps (FRSC) in Lokoja. After the training and testing of the dataset, we achieved an accuracy of 90.5%. The motorcycle accident severity prediction system developed could serve as a tool that can be used to cub the enormous challenges faced by FRSC in curtailing motorcycle accident.
Severity, Motorcycle, Accident, Knowledge Discovery, Decision Tree
To cite this article
Terungwa Simon Yange, Oluoha Onyekwere, Malik Adeiza Rufai, Charity Ojochogwu Egbunu, Onyinyechukwu Rehoboth Ogboli, Determination of the Severity of Motorcycle and Tricycle Accidents in Nigeria, Advances in Applied Sciences. Vol. 5, No. 2, 2020, pp. 41-48. doi: 10.11648/j.aas.20200502.14
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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