Many approaches have been proposed for decision criteria to judge whether or not transfer of bioanalytical methods has been successful.
Different qualitative models have been proposed for decision under uncertainty in Artificial Intelligence, but they generally fail to satisfy the principle of strict Pareto dominance or principle of "efficiency", in contrast to the classical numerical criterion expected utility.
Many multiple-criteria decision-making (MCDM) methods have been proposed for decision-making environments.
In recent years, artificial intelligence-based decision algorithms have been proposed for adaptive decision.
An approach, termed "GeoInsight" is proposed for characterizing decision making functions in a multi-agent system (MAS).
While there is a paucity of research that takes into account different aspects of this complex decision situation, only a limited number of mathematical models have been proposed for such decisions.
A large number of optimization techniques have been proposed for supporting decisions of MSW management and evaluating relevant operation and investment policies; they involve linear, dynamic, integer and multiobjective programming methods (Baetz, 1990; Lund et al. 1994; Masui et al. 2000; Kollikkathara et al. 2010; Cao and Huang, 2011).
The results show the importance of the proposed tools for decision making problems.
First, the performance of HMEM with heuristic context clusters is examined; second, the impact of the proposed method for decision tree-based context clustering presented in the Section 3.3 is evaluated.
Many methods have been proposed for multi-criteria decision making.
Iterative "learning" by distributed control agents has been proposed for power system decision making.
