Pythagorean back to the data type card17 methods
Pythagorean
Methods that work with Pythagorean 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.
18 academy cards · 0 only in the library · 17 methods in the catalogue
Methods with an academy card
18 cards- TOPSIS extensionsPythagorean fuzzy TOPSISThis is the Pythagorean fuzzy form of TOPSIS. The support and rejection degrees given to a judgement may sum to more than 1, provided the sum of their squares does not. The output is again a single closeness measure and a rank, built relative to the ideal and the anti-ideal.Open the card →
- VIKOR extensionsPythagorean fuzzy VIKORThis is the Pythagorean fuzzy form of VIKOR. The support and rejection degrees given to a judgement may sum to more than 1, provided the sum of their squares does not. The output is again group utility, individual regret, and a compromise index combining the two.Open the card →
- SAW extensionsPythagorean fuzzy SAWThis is the Pythagorean fuzzy form of SAW. The support and rejection degrees given to a judgement may sum to more than 1, provided the sum of their squares does not. This pair is carried through the whole calculation, and comes down to a single weighted score only at the last step.Open the card →
- EDAS extensionsPythagorean fuzzy EDASThis is the Pythagorean fuzzy form of EDAS. The sum of the support and rejection degrees given to a judgement may exceed 1, provided the sum of their squares does not. The output is again a single closure ratio built relative to the set's own average, and the ranking that follows from it.Open the card →
- EDAS extensionsCubic Pythagorean fuzzy EDASThis is the form of EDAS for situations where a criterion assessment is given both as an interval and as a single point. Every cell carries a Pythagorean interval AND a Pythagorean point together; the method combines the two into a single score and ranks alternatives against the set's average.Open the card →
- COPRAS extensionsPythagorean fuzzy COPRASThis is the Pythagorean fuzzy form of COPRAS. The sum of the support and rejection degrees given to a judgement may exceed 1, provided the sum of their squares does not. The output is again a benefit degree expressed as a percentage relative to the best alternative.Open the card →
- MARCOS extensionsPythagorean fuzzy MARCOSThis is the Pythagorean fuzzy form of MARCOS. The support and rejection degrees given to a judgement may sum to more than 1, provided the sum of their squares does not. The output is again a ratio built relative to the ideal and the anti-ideal, combined into a single utility degree.Open the card →
- CODAS extensionsPythagorean fuzzy CODASThis is the Pythagorean fuzzy form of CODAS. The sum of the support and rejection degrees given to a judgement may exceed 1, provided the sum of their squares does not. The output is again an assessment score built from two different distance measures to the negative-ideal, and the ranking that follows from it.Open the card →
- PROMETHEE extensionsPythagorean fuzzy PROMETHEEThis is the form of PROMETHEE for situations where the support and rejection degrees given to a judgement may sum to more than 1, provided the sum of their squares does not. The output is again a net flow built from the incoming and outgoing flows, and a rank based on this flow.Open the card →
- TODIM extensionsPythagorean fuzzy TODIMThis is the Pythagorean fuzzy form of TODIM. The support and rejection degrees given to a judgement may sum to more than 1, provided the sum of their squares does not. The loss-aversion logic runs on these pairs and comes down to a single global value.Open the card →
- WASPAS extensionsPythagorean fuzzy WASPASThis is the form of WASPAS for situations where the support and rejection degrees given to a judgement can together exceed 1, provided only that the sum of their squares does not exceed 1. The weighted-sum and weighted-product components are calculated separately over these support-rejection pairs, and only descend to a single score at the very last step.Open the card →
- ARAS extensionsPythagorean fuzzy ARASPythagorean fuzzy ARAS is the form of ARAS used when criterion assessments are given as a membership and non-membership degree pair, and the sum of these two degrees is permitted to exceed 1 provided the sum of their squares does not. It computes the additive utility ratio over these pairs, reducing the result to a single degree of utility.Open the card →
- MABAC extensionsPythagorean fuzzy MABACThis is the form of MABAC for situations where criterion scores are given as support and rejection degrees for a judgement, and the sum of these two degrees may exceed 1. It builds the border approximation area on a score derived from these two degrees, and ranks the result, once again, with a single figure.Open the card →
- MOORA extensionsPythagorean fuzzy MOORAThis is the Pythagorean fuzzy form of MOORA. The support and rejection degrees given to a judgement may sum to more than 1, provided the sum of their squares does not. The ratio system runs on this pair and comes down to a single net score.Open the card →
- GRA extensionsPythagorean fuzzy GRAThis is the form of GRA that works for situations where criterion scores are given as the degree to which a judgement is supported and rejected, and the sum of these two degrees can exceed 1. It computes the distance to the reference from these two degrees, and ranks the result again with a grey relational grade.Open the card →
- CoCoSo extensionsPythagorean fuzzy CoCoSoThis is the form of CoCoSo for situations where the sum of the support and rejection degrees given to a judgement may exceed 1, but the sum of their squares does not exceed 1. Its output is again a combined compromise score and the ranking that follows from it.Open the card →
- WPM extensionsPythagorean fuzzy WPMPythagorean fuzzy WPM is the form of WPM used when criterion values are recorded as a support and rejection degree (μ, ν) given to a judgement. The sum of the squares of these two degrees does not exceed 1. Its output is a Pythagorean score for every alternative and the rank that follows from it.Open the card →
- ELECTRE II extensionsPythagorean fuzzy ELECTRE IIThis is the form of ELECTRE II for situations where decision-makers give criterion scores as Pythagorean fuzzy pairs carrying both strong support and marked reservation, and several experts' opinions are assessed together. The output is again a ranking built from two directions.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.