Bayesian network of traffic accidents in Malaysia. Journal of Information and Communication Technology (JICT), 18 (4). pp. 473-484. ISSN 2180-3862 (2019)
Abstract
Exploring the causes and effects of a hazardous event such as traffic accidents have been of vital importance to society. Statistical analyses have been widely implemented to understand and deduce inferences on the cause-effect analysis, and to anticipate the occurrences of accidents in the future. One of the issues that has not been solved through conventional statistical modelling is the existence of interrelationships between variables in the data set. However, with the advent of technology and the wide application of machine learning algorithm, this problem can be solved through the application of Bayesian network analysis, which is a directed acyclic probabilistic graphical model. By using Hill Climb (HC) and Tabu algorithms, the structure of the data was studied and the relationship was estimated through conditional probability, that is based on the Bayes’ theorem.
| Item Type: | Article |
|---|---|
| Keywords: | Bayesian network, HC algorithm, Tabu algorithm, Traffic accidents |
| Taxonomy: | By Subject > Computer & Mathematical Sciences > Computer Science By Subject > Computer & Mathematical Sciences > Statistics |
| Local Content Hub: | Subjects > Computer and Mathematical Sciences |
| Depositing User: | Muslim Ismail @ Ahmad |
| Date Deposited: | 23 Feb 2021 03:11 |
| Last Modified: | 23 Feb 2021 03:11 |
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