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The study is from a base of accident scenarii in rail transport (feedback) inorder to develop a tool to share build and sustain knowledge and safety andsecondly to exploit the knowledge stored to prevent the reproduction ofaccidents / incidents. This tool should ultimately lead to the proposal ofprevention and protection measures to minimize the risk level of a newtransport system and thus to improve safety. The approach to achieving thisgoal largely depends on the use of artificial intelligence techniques andrarely the use of a method of automatic learning in order to develop afeasibility model of a software tool based on case based reasoning (CBR) toexploit stored knowledge in order to create know-how that can help stimulatedomain experts in the task of analysis, evaluation and certification of a newsystem.

Contribution of Case Based Reasoning (CBR) in the Exploitation of Return of Experience. Application to Accident Scenarii in Railroad Transport