A Selection of Useful Patterns Based on Multi-Criteria Analysis Approach

Mazouri, Fatima Zahra El; Abounaima, Mohammed Chaouki; Zenkouar, Khalid

doi:10.1145/3167486.3167517

Cited by 6 publications

(2 citation statements)

References 28 publications

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“…DM techniques are used in different research domains and areas and have provided useful results to extract the hidden knowledge for the decision makers. For instance, we can find in [11][12][13][14] several researches and studies on the application of the association rules for various problems, and in particular the problem of safety of the road traffic [15][16][17][18][19][20][21]. Besides, according to the national observatory of road safety [22][23][24], at least 350,000 people died since 1960 as a result of a road accident in France: in 1972, there were 18,034 official deaths.…”

Section: Introductionmentioning

confidence: 99%

Data mining combined to the multicriteria decision analysis for the improvement of road safety: case of France

2019

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Introduction: The problem studied in this paper is the road insecurity, which is manifested by the big number of injuries and deaths recorded annually around the world. These victims of road accidents worry the whole community, hence the duty and the need to find solutions for reducing the number of victims and material damage. The overall purpose of this case study is to treat the problem of corporeal accidents known in France. Case description: The case study presented in this paper is intended to help decisionmakers to find and understand the all significant relationships and correlations that exist between the conditions that led to these corporeal accidents. In fact, the two French ministries of interior and transport have jointly created a unique database on corporeal accidents, called BAAC "Accident Analysis Bulletin Corporal", with the aim of allowing different exploitations of this database by different concerned administrations and research organizations. Our intervention consists to adopt a hybrid approach based on data mining techniques combined to the multicriteria decision methods. This approach allows to extract the most relevant association rules. The results thus obtained can be easily exploited by the decision-makers to choose the appropriate policies in the perspective of improving road safety. Discussion and evaluation: The proposed approach ranks all association rules in order of importance for several quality measures of association rules. The alternatives at the top of the ranking are the results to retaining for the analysis. The approach is applied to the BAAC database of 2016, which led to the selection of three association rules. These association rules reveal that there are narrow correlations between the following elements: Driver with Pedestrian, Normal Surface of Road with Normal Atmospheric Condition and the Pavement with Pedestrian. These correlations can be justified by excess speed and carelessness of the drivers. Conclusion: The improvement of the road safety needs mainly to work more intensively on the behavioral side of the road users. For future work, it is planned to apply the proposed approach to the French traffic accident database, containing all the data on road accidents collected over several years. In addition, other measures will be used in the ranking of the association rules.

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Section: Introductionmentioning

confidence: 99%

Data mining combined to the multicriteria decision analysis for the improvement of road safety: case of France

2019

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“…Medical applications: [24] j. Automatic Image Annotation: [14] k. Data Mining and Big Data: [7] l. Etc. The list of applications listed below is obviously not exhaustive.…”

Section: The Electre Methods Familymentioning

confidence: 99%

Application of the ELECTRE III Method at the Moroccan Rural Electrification Program

Mazouri¹,

Abounaima²,

Zenkouar³

et al. 2018

IJECE

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<p>As part of the integrated strategy of the Moroccan state aimed at the social and economic development of the Moroccan rural community, an electrification program has been in place since the 90s. This program, called PEGR, has for main objective the improvement of the electrification rate for the national rural world. Given the large number of villages to be electrified and the colossal budget that will induce, several criteria have been retained to objectively distinguish the villages with the highest priority for electrification. Given the nature of this problem to be solved, which is a multicriteria decision aid problem, we propose in this article to use the multicriteria aggregation method ELECTRE III to rank the villages from the highest priority to the lowest priority for the electrification.</p>

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AC.Rank_A : Rule Ranking Method via Aggregation of Objective Measures for Associative Classifiers

Dall’Agnol,

Carvalho

2024

IEEE Access

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A Selection of Useful Patterns Based on Multi-Criteria Analysis Approach

Cited by 6 publications

References 28 publications

Data mining combined to the multicriteria decision analysis for the improvement of road safety: case of France

Data mining combined to the multicriteria decision analysis for the improvement of road safety: case of France

Application of the ELECTRE III Method at the Moroccan Rural Electrification Program

AC.Rank_A : Rule Ranking Method via Aggregation of Objective Measures for Associative Classifiers

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A Selection of Useful Patterns Based on Multi-Criteria Analysis Approach

Cited by 6 publications

References 28 publications

Data mining combined to the multicriteria decision analysis for the improvement of road safety: case of France

Data mining combined to the multicriteria decision analysis for the improvement of road safety: case of France

Application of the ELECTRE III Method at the Moroccan Rural Electrification Program

AC.RankA : Rule Ranking Method via Aggregation of Objective Measures for Associative Classifiers

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Product

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AC.Rank_A : Rule Ranking Method via Aggregation of Objective Measures for Associative Classifiers