A novel adaptive control method is proposed for controlling newly introduced uncertain unified system.
Some recent researches have introduced uncertain graphs whose edges are labeled with a probability of existence [41, 42].
An interpretation of label semantics is then proposed which incorporates prototype theory by introducing uncertain thresholds on the distance between elements and prototypes for description labels.
A common objection to the issue of simulation models is that their estimates come at the cost of introducing uncertain assumptions (6).
In view of highly uncertain characteristics of decision attribute value in the practical process, we introduce the uncertain linguistic multiple attribute decision making (ULMADM) method in the function allocation process.
This is a simplification since tax rates can be observed to have an uncertain element and they often depend on certain characteristics of agents such is their income.3 Introducing an uncertain tax rate may introduce an additional covariance as well as an expectation into the pricing equation.
First, fuzzy mathematical programming is introduced for uncertain modeling.
In Section 2, we introduce the uncertain multiobjective linear programming problems and the concept of robust efficient solution to UMLP.
We have shown (Fig. 1 (right)) that introducing many uncertain allele calls leads to ltLRs that satisfy the bound, which is reasonably tight with as few as three replicates even when 80% of true alleles are designated as uncertain and there are also multiple uncertain non-alleles.
This strategy introduces useful but uncertain features and produces a large number of features.
