| Autor: |
Koichiro Ochimizu, Nyein Thwet Thwet Aung, Swe Zin Hlaing, Kyi Pyar Hlaing |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
2019 International Conference on Advanced Information Technologies (ICAIT). |
| DOI: |
10.1109/aitc.2019.8921119 |
| Popis: |
Road accidents are unpredictable and undetermined occurrence. Analysis of road accidents needs to understand the factor causing road accident severity. Careful analysis of road accident record is important to find out leading indicator factor for road accident. This paper introduces the analysis of severity factor using Functional Resonance Analysis Method (FRAM) that can be used an accident analysis method providing a new concept for people to analyze accidents. It also applies Naive Bayes (NB) Algorithm is one of the classification techniques and based on probability models that incorporate strong independence assumptions. In this paper, firstly, FRAM shows the model of analysis of road accident. Secondly NB algorithm applies to calculate the probability of severity level attribute. Finally, this paper shows some experiment of the real dataset of road accident in Yangon by applying the actual scenario. The result shows that the performance variability from the function of the model such as accident time, causes of accident reason and type of vehicle are important factor to lead the level of road accident severity. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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