English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

One of the most important aspects in any treatment of uncertain informationis the rule of combination for updating the degrees of uncertainty. The theoryof belief functions uses the Dempster rule to combine two belief functionsdefined by independent bodies of evidence. However, with limited dependencyinformation about the accumulated belief the Dempster rule may lead tounsatisfactory results. The present study suggests a method to determine theaccumulated belief based on the premise that the information gain from thecombination process should be minimum. This method provides a mechanism that isequivalent to the Bayes rule when all the conditional probabilities areavailable and to the Dempster rule when the normalization constant is equal toone. The proposed principle of minimum information gain is shown to beequivalent to the maximum entropy formalism, a special case of the principle ofminimum cross-entropy. The application of this principle results in a monotonicincrease in belief with accumulation of consistent evidence. The suggestedapproach may provide a more reasonable criterion for identifying conflictsamong various bodies of evidence.

Combination of Evidence Using the Principle of Minimum Information Gain