Comparison of Fuzzy and Neural Classifiers for Road Accidents Analysis

摘要

This paper investigates the classification of road accidents using neural networks and fuzzy clas- sification techniques. Accident correctability by road improvements has been advocated as an important criterion in the identification of accident-prone locations. Sayed et al. (1995) described a method to identify accident correctability using a fuzzy classification algorithm (fuzzy K-nearest neighbors). The method used safety experts' knowledge to classify accidents according to their contributing factors and causes into the three road-system components (the vehicle, the driver, and the road environment).