Approche générique d’aide à la décision pour l’amélioration de la sécurité des transports

Abstract : In the recent years, more and more businesses and industries have become aware of the increasing importance of competition imposed by the technological advances found in all areas and the continuous development of new information and communication technologies. Due to this situation and in order to maintain their competitiveness, these organizations have to adopt these more efficient technologies without any regard to constraints and security requirements. Consequently, numerous risks have arisen and facilitated the emergence of conflicting situations regarding safety. In some situations, failures are serious and costly due to accidents causing life loss, especially when it is a high-risk area such as transport field. The objective of this thesis is to propose a new approach based on artificial intelligence to predict accidents and help in taking the right decision to minimize risks. In this Decision-Aid (DA) approach, a coupling between the Case-Based Reasoning (CBR) and ontologies has been made to allow, taking into account certain criteria, assisting a decision maker (analyst, user, etc..) to understand a given risky situation and to propose to him possible solutions. The approach developed in this work, called ADAST (Aide à la Décision pour l’Amélioration de la Sécurité des Transports = decision aid to improve the transport safety) is a generic approach to decision aid for improving security analysis, which has been applied in the railroad transport. The significance of such an approach lies not only in the capitalization of knowledge (from experience feedback) but also in taking advantage of the know-how capable of stimulating and helping the domain experts in their task analysis and safety assessment.
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Ahmed Maalel. Approche générique d’aide à la décision pour l’amélioration de la sécurité des transports. Intelligence artificielle [cs.AI]. Ecole Nationale des Sciences de l'Informatique (ENSI), La Manouba (Tunisie), 2015. Français. ⟨tel-02343916⟩

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