Table 6 Feature analysis of different models with a proposed model.

From: Optimizing construction company selection using einstein weighted aggregation operators for q-rung orthopair fuzzy hypersoft set

 

Fuzzy information

MD

NMD

Parameterization

Sub-parameters

Advantages

FS1

✓

 × 

✓

 × 

 × 

Deals uncertainty by \(MD\)

IFS4

✓

 × 

✓

 × 

 × 

Deals uncertainty by \(MD + NMD > 1\)

PFS15

✓

 × 

✓

 × 

 × 

Deals uncertainty by \(MD\) and \(NMD\)

q-ROFS27

✓

✓

✓

 × 

 × 

Deals uncertainty by \(\left( {MD} \right)^{2} + \left( {NMD} \right)^{2} > 1\)

FSS34

✓

✓

 × 

✓

 × 

Deals uncertainty by using parametric values of \(MD\)

IFSS36

✓

✓

 × 

 × 

 × 

Deals uncertainty by parametric values of \(MD\) and \(NMD\);\(MD + { }NMD > 1\)

PFSS40

✓

✓

 × 

 × 

 × 

Deals uncertainty by if \(\left( {MD} \right)^{2} + \left( {NMD} \right)^{2} > 1\)

q-ROFSS46

✓

✓

✓

✓

 × 

Deals uncertainty by, if \(\left( {MD} \right)^{q} + \left( {NMD} \right)^{q} > 1\)

IFHSS49

✓

✓

✓

✓

✓

Deals uncertainty of multi sub-parameters such as \(MD + NMD > 1\)

PFHSS52

✓

✓

✓

✓

✓

Deals uncertainty of multi sub-parameters \(\left( {MD} \right)^{2} + \left( {{\text{NMD}}} \right)^{2} > 1\)

q-ROFHSS

✓

✓

✓

✓

✓

Deals uncertainty of multi sub-parameters \(\left( {{\text{MD}}} \right)^{{\text{q}}} + \left( {{\text{NMD}}} \right)^{{\text{q}}} > 1\)