Spherical back to the data type card19 methods
Spherical
Methods that work with Spherical 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 · 3 only in the library · 19 methods in the catalogue
Methods with an academy card
16 cards- TOPSIS extensionsSpherical fuzzy TOPSISSpherical fuzzy TOPSIS is the form of TOPSIS used when criterion scores are given as three separate numbers stating a degree of support, rejection and hesitancy for a judgement. The calculation comes down to a single closure ratio; a small value in this ratio shows closeness to the ideal.Open the card →
- VIKOR extensionsSpherical fuzzy VIKORSpherical fuzzy VIKOR is the form of VIKOR used when criterion scores are given as three separate numbers stating a degree of support, rejection and hesitancy for a judgement. Group utility and individual regret are carried through all three degrees, only scored at the very end, and combined with the same compromise logic.Open the card →
- SAW extensionsSpherical fuzzy SAWSpherical fuzzy SAW is the form of SAW used when criterion scores are given as three separate numbers stating a judgement's degree of support, rejection and hesitancy. The calculation still comes down to a single weighted sum at the end; a larger value is better.Open the card →
- EDAS extensionsSpherical fuzzy EDASSpherical fuzzy EDAS is the form of EDAS used when criterion scores are given as three separate numbers: a judgement's degree of support, rejection and hesitancy. Both the average solution and the deviations stay three-degree throughout; they drop to a single number only in the very last step.Open the card →
- COPRAS extensionsSpherical fuzzy COPRASSpherical fuzzy COPRAS is the form of COPRAS used when criterion scores are given as three separate numbers: a judgement's degree of support, rejection and hesitancy. Every cell drops to a single score within its constraint in the first step; the benefit and cost totals are then built on these scores exactly as in crisp COPRAS.Open the card →
- MARCOS extensionsSpherical fuzzy MARCOSSpherical fuzzy MARCOS is the form of MARCOS used when criterion scores are given as three separate numbers: a judgement's degree of support, rejection and hesitancy. Distance to the ideal and the anti-ideal is measured with an angular distance rather than a straight-line one.Open the card →
- CODAS extensionsSpherical fuzzy CODASThis is the form of CODAS for situations where criterion scores are given as three separate numbers: a judgement's degree of support, rejection and hesitancy; it still ranks the result with an assessment score.Open the card →
- PROMETHEE extensionsSpherical fuzzy PROMETHEEThis is the form of PROMETHEE for situations where criterion scores are given as a degree of support, a degree of rejection and a degree of hesitancy, each supplied separately by the expert. Because no direct difference can be taken between two spherical fuzzy numbers, the comparison runs through an intermediate closeness ratio.Open the card →
- TODIM extensionsSpherical fuzzy TODIMSpherical fuzzy TODIM is the form of TODIM for situations where criterion scores are given as three separate numbers stating a degree of support, rejection and hesitancy. It carries the same loss-aversion logic through a score and a distance built from these three degrees.Open the card →
- WASPAS extensionsSpherical fuzzy WASPASThis is the form of WASPAS used when criterion scores are given as three separate numbers stating a degree of support, rejection and hesitancy for a judgement. The weighted-sum and weighted-product components are calculated separately with these three degrees, and only come down to a single score at the very last step.Open the card →
- ARAS extensionsSpherical fuzzy ARASThis is the form of ARAS for situations where criterion scores are given as three separate numbers: a degree of support for a judgement, a degree of rejection, and a degree of hesitancy. It produces a ratio against the optimal alternative, but this ratio has a particular quirk that means it cannot be read as a percentage the way crisp ARAS's can; this is explained below.Open the card →
- MABAC extensionsSpherical fuzzy MABACThis is the form of MABAC used when criterion scores are given as three separate numbers: a judgement's degree of support, rejection and hesitancy. It builds the border approximation area on a score derived from these three degrees, and still ranks the result with a single score.Open the card →
- MOORA extensionsSpherical fuzzy MOORASpherical fuzzy MOORA is the form of MOORA's ratio system for situations where criterion scores are given as a support-rejection-hesitancy triple. Its output remains a single score and the rank that score produces.Open the card →
- GRA extensionsSpherical fuzzy GRAThis is the form of GRA used when criterion scores are given as three separate numbers: a judgement's degree of support, rejection and hesitancy. Its output remains a grey relational grade and the rank that grade produces.Open the card →
- CoCoSo extensionsSpherical fuzzy CoCoSoThis is the form of CoCoSo for situations where criterion scores are given as three separate numbers: a judgement's degree of support, rejection and hesitancy. Its output remains a combined compromise score and the rank that score produces.Open the card →
- WPM extensionsSpherical fuzzy WPMSpherical fuzzy WPM is the form of WPM used when criterion scores are given as three separate numbers stating a degree of support, rejection and hesitancy for a judgement. The calculation first reduces every cell to a single number, then multiplies these numbers together with weights.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.