The MAFU is designed to be a new insight for transportation decision-making through the visual and complex preference trade-offs, and criteria uncertainty and an open-ended approach, which can integrate additional evaluation criteria and performance attributes as needed.
In order to be diagnosed as having CP participants had to meet the following criteria: Uncertainty in face recognition: Not recognizing familiar people unexpectedly or in crowed places, confusing unknown persons with familiar persons.
In order to be diagnosed with CP, participants had to meet the following criteria: Uncertainty in face recognition: Not recognizing familiar people unexpectedly or in crowded places, confusing unknown persons with familiar persons.
The method sections of the retrieved articles were examined to assess whether they satisfied the inclusion criteria; uncertainty was resolved by asking a co-researcher for independent assessment.
In this manuscript, we describe a procedure that allows robust application of the MFA, including model selection criteria, uncertainty calculations, and other procedures for analyzing a SM-SR data set and image reconstruction.
The focus of this paper is the MAFU process conducted in Level 3. MAFU is a multi-attribute, multi-criterion and multi-objective evaluation and decision-making process employing fuzzy mathematics to capture the trade-offs of stakeholder preferences, utility theory to describe risk sensitivity, and probabilistic approach to model criteria uncertainties.
Another suggestion was to divide the criterion of uncertainty (C) into two or more criteria that would identify different kinds of uncertainties.
Then using Sylvester's criterion, new uncertainty conditions are developed.
Quite a lot research has been carried out in this regard in which for most of the proposed algorithms, kriging variance minimization as a criterion for uncertainty assessment is defined as objective function and the problem could be solved through optimization methods.
Analytic Hierarchy Process (AHP) is an efficient decision making tool for complicated problems with multiple evaluation criteria and uncertainty.
This paper examines a new multi-objective mathematical model in a Dynamic Cell Formation Problem (DCFP), where social criteria and uncertainty conditions are considered.
