Sentence examples for experts preference from inspiring English sources

The consensus and proximity measures are calculated by using the relative projections of experts' preference relations respectively.

Such MEMs can be used as a decision basis for the designer or they can be included into structural optimization in order to find Pareto optimal solutions, representing the experts' preference of structural vs. manufacturing criteria.

This paper presents a consensus model for group decision making with interval multiplicative and fuzzy preference relations based on two consensus criteria: (1) a consensus measure which indicates the agreement between experts' preference relations and (2) a measure of proximity to find out how far the individual opinions are from the group opinion.

For experts' preferences represented by reciprocal fuzzy preference relations, consistency is linked to the transitivity property.

The experts' preferences over the set of alternatives are represented as linguistic terms instead of numerical values.

To overcome such a limitation, the experts' preferences in the GEDM problem are considered as the group hesitation about the alternatives and they will be fused by utilizing a HFS to keep as much information as possible.

As a result, it allows users to calculate total scores on ORACLe that are context-sensitive, appropriate, and in line with experts' preferences.

To overcome this lack of precision, FAHP makes the comparison process more flexible for eliciting experts' preferences (Kahraman et al., 2003; Kutlu and Ekmekçioglu., 2012).

Methods: the study was articulated in the following four stages: (i) Item generation based on literature review, sarcopenic subjects' opinion, experts' opinion, focus groups; (ii) Item reduction based on sarcopenic subjects' and experts' preferences; (iii) Questionnaire generation developed during an expert meeting; (iv) Pretest of the questionnaire based on sarcopenic subjects' opinion.

By applying the discrete choice approach in our study, we were able to establish experts' preferences regarding which capacity domains represented more important organisational tools and supports to facilitate research use, and obtain utilities for each capacity domain in order to calculate total scores.

In turn, these modes optimize the camera parameters, based on extensive expert preference models.