  The study is from a base of accident scenarii in rail transport (feedback) in
order to develop a tool to share build and sustain knowledge and safety and
secondly to exploit the knowledge stored to prevent the reproduction of
accidents / incidents. This tool should ultimately lead to the proposal of
prevention and protection measures to minimize the risk level of a new
transport system and thus to improve safety. The approach to achieving this
goal largely depends on the use of artificial intelligence techniques and
rarely the use of a method of automatic learning in order to develop a
feasibility model of a software tool based on case based reasoning (CBR) to
exploit stored knowledge in order to create know-how that can help stimulate
domain experts in the task of analysis, evaluation and certification of a new
system.
