Table 14 CN-LDFS comparison research with previous methods.

From: Framework development of continuous non-linear Diophantine fuzzy sets and its application to renewable energy source selection

Collection

Remarks

Parametrization

Continuous environment

FS1

Unable to deal about non-membership ν

NO

NO

IFS16

cannot deal with the condition, μ + ν > 1

NO

NO

PyFS17

cannot deal with the condition,\({\mu }^{2}+{\nu }^{2}>1\)

NO

NO

q-ROFS18

Smaller "q" values cannot be handled under the conditions \({\mu }^{q}+{\nu }^{q}>1\) and for \(\mu =1,\) \(\nu =1\)

NO

NO

LDFS28

Cover the condition that,\(0\le \left(\varphi \right)\mu \left(\sigma \right)+\left(\gamma \right) \nu \left(\sigma \right)\le 1\)

YES

NO

N-LDFS31

Provided the qth power to LDFS and makes is it N-LDFS

YES

NO

Current study (CN-LDFS)

Proposed work cover all the limitations of parametrization and continuous environment

YES

YES