In this paper results of accidents classification using fuzzy cluster algorithms are reported. The object of clustering is to divide a given data set into homogeneous groups, that is all accidents in the same cluster share similar attributes and they do not share similar attributes with accidents in other clusters. The process was carried out using the fuzzy k-means method with extragrades. The basic idea is to classify accidents according to their patterns and causes into one or a conbination of classes recognizing the complex interaction among accident factors and the uncertainties associated with accident data. The object of the study are the accidents happened along the highway A3 Naples-Salerno during the period August 1998 - March 2000. The characterizations of the accidental events have been encoded, to the purposes of the elaborations, through variables whose values are represented by theirs levels.

Highway Accidents Analysis Using Fuzzy Pattern Recognition

DELL'ACQUA, GIANLUCA
2002

Abstract

In this paper results of accidents classification using fuzzy cluster algorithms are reported. The object of clustering is to divide a given data set into homogeneous groups, that is all accidents in the same cluster share similar attributes and they do not share similar attributes with accidents in other clusters. The process was carried out using the fuzzy k-means method with extragrades. The basic idea is to classify accidents according to their patterns and causes into one or a conbination of classes recognizing the complex interaction among accident factors and the uncertainties associated with accident data. The object of the study are the accidents happened along the highway A3 Naples-Salerno during the period August 1998 - March 2000. The characterizations of the accidental events have been encoded, to the purposes of the elaborations, through variables whose values are represented by theirs levels.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/183623
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