Data Fusion, Ensemble and Clustering for the Severity Classification of Road Traffic Accident in Korea

데이터융합, 앙상블과 클러스터링을 이용한 교통사고 심각도 분류분석

Increasing amount of road tragic in 90's has drawn much attention in Korea due to its influence on safety problems. Various types of data analyses are done in order to analyze the relationship between the severity of road traffic accident and driving conditions based on traffic accident records. Accurate results of such accident data analysis can provide crucial information for road accident prevention policy. In this paper, we apply several data fusion, ensemble and clustering algorithms in an effort to increase the accuracy of individual classifiers for the accident severity. An empirical study results indicated that clustering works best for road traffic accident classification in Korea.