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使用多标准决策支持系统改进的关联规则挖掘方法：道路安全案例研究

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

作者：Addi Ait-Mlouk;Fatima Gharnati;Tarik Agouti;

关键词：Data mining,Association rules,Road accident,Quality measurements,Multi-criteria decision analysis

DOI：https://doi.org/10.1007/s12544-017-0257-5

发表时间：2017年

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摘要

目的道路事故已被视为全球重大公共卫生问题。因此，许多研究的目的是确定导致事故严重程度的主要因素。方法本文研究了一种称为关联规则挖掘的大规模数据挖掘技术，该技术可以提前预测未来的事故并让驾驶员避免危险。然而，这种技术会产生大量的决策规则，导致决策者无法自己选择最相关的规则。在这种情况下，多标准决策分析方法的集成对于受提取规则冗余影响的决策者特别有用。结论对马拉喀什省（摩洛哥）道路事故的分析) 2004 年至 2014 年期间的情况表明，拟议的方法符合此目的；它可能提供有意义的信息，有助于制定适当的预防政策以改善道路安全。


Abstract

PurposeRoad 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.MethodsThis 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.ConclusionAn 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.


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