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Technique for order preference by similarity to ideal solution (TOPSIS) is used for ranking these materials.
Moreover, DR programs are prioritized by using the technique for order preference by similarity to ideal solution method.
In this work, firstly the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is described.
The approach incorporates Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).
A comparison with the classical method and fuzzy technique for order preference by similarity of an ideal solution (FTOPSIS) is discussed.
The rank of RFs is obtained by using the extent fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS).
We establish the SMAA-TOPSIS model by combining stochastic multicriteria acceptability analysis (SMAA) and technique for order preference by similarity to ideal solution (TOPSIS).
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We provide a semantics for our first-order preference language in the situation calculus, and prove that progression of our preference formulae preserves this semantics.
We predict that managers' honesty will be improved when the beneficiaries of the slack have a known, higher-order preference for truthful reporting.
This is consistent with state mania augmenting the role that lower-order preference plays in the evaluation of gain outcomes in ventromedial PFC.
We evaluated the degree to which activity in ventral striatum (lower-order preference) and dorsolateral PFC (long-term goal) predicted activity in ventromedial PFC (weighted by both lower-order preference and the long-term goal), and how this differed between groups.
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