An improved approach for association rule mining using a multi-criteria decision support system: a case study in road safety

PURPOSE: Road accidents have come to be considered a major public health problem worldwide. The aim of many studies is therefore to identify the main factors contributing to the severity of crashes. METHODS: This paper examines a large-scale data mining technique known as association rule mining, which can predict future accidents in advance and allow drivers to avoid the dangers. However, this technique produces a very large number of decision rules, preventing decision makers from making their own selection of the most relevant rules. In this context, the integration of a multi-criteria decision analysis approach would be particularly useful for decision makers affected by the redundancy of the extracted rules. CONCLUSION: An analysis of road accidents in the province of Marrakech (Morocco) between 2004 and 2014 shows that the proposed approach serves this purpose; it may provide meaningful information that could help in developing suitable prevention policies to improve road safety.

Language

  • English

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  • Accession Number: 01642666
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 28 2017 1:37PM