A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
Approaches for Managing Uncertainty in Learning Management Systems
2016
Egyptian Computer Science Journal
unpublished
The notion of uncertainty in expert systems is dealing with vague data, incomplete information, and imprecise knowledge. Different uncertainty types which are imprecision, vagueness, ambiguity, and inconsistence need different handling models. Uncertain knowledge representation and analysis is an essential issue. Classical probability, Bayes theory, Dempster-Shafer theory, certainty factor and fuzzy set approaches presented in expert systemsfor managing uncertainty data, but these models are
fatcat:jbebnianubghji6yb2hsuupgju