Abstract
In this paper, a new mathematical procedure is presented for combining different pieces of evidence which are represented in the interval form to reflect our knowledge about the truth of a hypothesis. Evidence may be correlated to each other (dependent evidence) or conflicting in support (conflicting evidence). First, assuming independent evidence, we propose a methodology to construct combination rules which obey a set of essential properties. The method is based on a geometric model. We compare results obtained from the Dempster—Shafer rule, interval Bayes rule, and the proposed combination rules with both conflicting and nonconflicting data and show that the values generated by the proposed combining rules are in tune with our intuition in both cases. Secondly, in the case that evidence is known to be dependent, we consider extensions of the rules derived for handling conflicting evidence. The performance of proposed rules are shown by different examples. The results show that the proposed rules reasonably make decisions under dependent evidence.
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.
