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

We are concerned with three types of uncertainties: probabilistic,possibilitistic and interval. By using possibility and necessity measures as anInterval Valued Probability Measure (IVPM), we present IVPM's interval expectedvalues whose possibility distributions are in the form of polynomials. Byworking with interval expected values of independent uncertainty coefficientsin a linear optimization problem together with operations suggested in Lodwickand Jamison (2007), the problem after applying these operations becomes alinear programming problem with constant coefficients. This is achieved by theapplication of two functions. The first is applied to the intervalcoefficients, v: I -> R^k, where I= {[a,b] | a <= b}. The second is u: R^k ->R, applied to the product we got from a previous function. Similar conceptshold for any types of optimization problems with linear constraints. Moreover,it implied that optimization problems containing all three types ofuncertainties in one problem can be solved as ordinary optimization problems.

Algorithm for solving optimization problems with Interval Valued Probability Measure