Abstract
This paper presents an intelligent support of decision making to improve security analysis called Adast. The adopted approach in this research is based on acquiring and reusing past accident scenarii, historically validated on other homologated transport systems. The advantage of this approach, based primarily on Case-Based Reasoning (CBR) and ontologies, lies not only on the capitalization of knowledge from experience feedback, but also on benefit in order to provide assistance to domain experts in their crucial task of analyzing and improving security. Also, the problems of knowledge and case representation are considered in this paper. A prototype of intelligent decision support system based on Adast has been implemented to better integrate the proposed CBR cycle and ontology.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
