Linguistic back to the data type card13 methods
Linguistic
Methods that work with Linguistic data
Every method that works with this data type has a page of its own. Those with an academy card are explained here through their philosophy, how to read their output and worked cases; the rest open on their formula page in the library.
16 academy cards · 0 only in the library · 13 methods in the catalogue
Methods with an academy card
16 cards- TOPSIS extensions2-tuple linguistic TOPSISThis is the form of TOPSIS for situations where expert scores are chosen from a pre-declared term set, and where the aggregation result is preserved with its shift rather than rounded to a term.Open the card →
- TOPSIS extensionsProbabilistic linguistic TOPSISThis is the form of TOPSIS for situations where an expert gives several terms together with their probabilities. It reduces every term distribution to a single expected value, then ranks the result with a closeness score as usual.Open the card →
- VIKOR extensions2-tuple linguistic VIKORThis is the form of VIKOR for situations where expert scores are chosen from a pre-declared term set, and where the aggregation result is preserved with its shift rather than rounded to a term.Open the card →
- VIKOR extensionsProbabilistic linguistic VIKORThis is the form of VIKOR for situations where an expert gives several terms together with their probabilities. It reduces every term distribution to a single expected value, then ranks the result with a compromise proposal as usual.Open the card →
- SAW extensions2-tuple linguistic SAWThis is the form of SAW for situations where expert scores are chosen from a pre-declared term set, and where the aggregation result is preserved with its shift rather than rounded to a term.Open the card →
- EDAS extensionsProbabilistic Linguistic EDASThis is the form of EDAS for situations where expert scores are given not as a single word but as the probabilities of several linguistic terms. Every cell is first reduced to an expected linguistic value, and the ranking against the average runs on these values.Open the card →
- EDAS extensions2-tuple linguistic neutrosophic EDAS2-tuple linguistic neutrosophic EDAS is the form of EDAS for situations where criterion assessment is made in words chosen from a term set, with a degree of truth, indeterminacy and falsity attached to those words. The combined result is not rounded to a term; it is carried together with its term and translation value.Open the card →
- EDAS extensionsLinguistic Pythagorean fuzzy EDAS (CRITIC-weighted)Linguistic Pythagorean fuzzy EDAS is the form of EDAS where criterion assessment is done with support and rejection degrees chosen from a term set, and criterion weights are derived not from an expert but from the data itself, by the CRITIC method.Open the card →
- COPRAS extensions2-tuple linguistic COPRASThis is the form of COPRAS for situations where criterion values are given in words chosen from a pre-declared term set, and the calculation is carried out without converting these terms into numbers, through a lossless representation. The output is again a percentage relative to the best alternative and a ranking based on that percentage.Open the card →
- MARCOS extensionsProbabilistic Linguistic MARCOSThis is the form of MARCOS for situations where expert scores are given not as a single word but as the probabilities of several linguistic terms. Every cell is first reduced to an expected linguistic value, and the utility ratio against the ideal and anti-ideal is built on these values.Open the card →
- CODAS extensions2-tuple linguistic CODASThis is the form of CODAS for situations where expert scores are chosen from a pre-declared term set, and the two distances to the negative-ideal are computed carrying the symbolic translation value rather than rounding to a single term.Open the card →
- TODIM extensions2-tuple linguistic TODIMThis is the form of TODIM for situations where criterion scores are chosen from a pre-declared term set, and where the aggregation result is preserved with its shift rather than rounded to a term.Open the card →
- TODIM extensionsProbabilistic linguistic TODIMProbabilistic linguistic TODIM is the form of TODIM for situations where an expert judges a criterion not with a single word but with an opinion spread across several terms. It reduces the term distribution to an expected value and ranks alternatives with the same loss-aversion logic.Open the card →
- MABAC extensionsProbabilistic linguistic MABACThis is the form of MABAC for situations where the expert gives several terms together with their probabilities. Every term distribution is reduced to a single expected value, and the result is still ranked by a score relative to the border approximation area.Open the card →
- MULTIMOORA extensions2-tuple linguistic MULTIMOORA2-tuple linguistic MULTIMOORA is the form of MULTIMOORA for situations where a criterion score is given as a term chosen from a pre-declared term set together with a shift away from that term. The ratio system, the reference point and the full multiplicative form are each computed on these terms separately, and the three sub-rankings are merged into a single order by dominance theory.Open the card →
- MULTIMOORA extensionsProbabilistic linguistic MULTIMOORAProbabilistic linguistic MULTIMOORA is the form of MULTIMOORA for situations where a criterion assessment is split across several terms and the probabilities of those terms. The ratio system, the reference point and the full multiplicative form are all computed on the same expected value; the result is combined with an improved Borda score.Open the card →
Other methods in the library
These methods do not yet have an academy card. Their formulae, steps and source citation live in the library; each link opens the method page directly.
No method without a card remains for this type.