Multiple Classifier of Traffic Accident Based on Matter-Element Analysis
| Autor: | Chao Sun, Wei Quan |
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| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | IOP Conference Series: Earth and Environmental Science. 587:012038 |
| ISSN: | 1755-1315 1755-1307 |
| Popis: | The paper establishes a new multiple classifier for grading the traffic accident based on the Hard Decision Model and the parallel topological structure. Logistic Regression, decision tree(DT) and BP Neural Network are selected as the base classifiers and matter-element analysis is employed as the fusion algorithm to improve the traditional topological structure. Matter-Element analysis has potential to increase the objectivity and dynamic in the criterion setting of the multiple classifier by combining the confidence coefficient of the base classification results. The accuracies of different base classifiers are used for weight factors calculation instead of the analytic hierarchy process (AHP) or the fuzzy synthetic evaluation (FSE) to avoid the influence of human factors. 200 recordings of the traffic accident are selected as a case study for methodology verification. The results show that compared with the base classifiers, the capacity to identify the class of traffic accident can be strengthened apparently by the multiple classifier based on confidence coefficient and Matter-Element Analysis Meanwhile, this classifier provides the best opportunity to avoid many bad conditions of single model, such as overfitting and under-fitting. |
| Databáze: | OpenAIRE |
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