Intuitionistic Fuzzy Aggregation Techniques - Intuitionistic Fuzzy Aggregation and Clustering - page 139

⎛

w j ⎞
⎠

1

1
ρ

μ F n

m

− μ F n

⎝ 1

− ≥ min

j

(1.350)

κ α j ,λ α j ( α j )

κα j ,λα j ( α j

)

j = 1

1 1 ρ w j 1 1 v F n ρ w j

m m

− − v F n ≤ − − max

j

κ α j ,λ α j ( α j

)

κ α j ,λ α j ( α j

)

j = 1 j = 1

1 v F n ρ

= 1 − − max

j

(1.351)

κ α j ,λ α j ( α j )

1

) ) ρ w j

1 v F n ρ

m

1 − − ( 1 − v F n ≥ − max

j

κ α j ,λ α j ( α j κ α j ,λ α j ( α j

)

j = 1

(1.352)

⎛

ρ w j ⎞
⎠

1
ρ

1 1 v F n

m

⎝ 1

− − − v F n ≥ 1 − max

j

κα j ,λα j ( α j

)

κα j ,λα j ( α j

)

j = 1

(1.353)

⎛

η w j ⎞
⎠

1
ρ

1 1 v F n

m

⎝ 1

1 − − − − v F n ≤ max

j

κ α j ,λ α j ( α j

)

κ α j ,λ α j ( α j

)

j = 1

(1.354)

Similarly, we have

⎛

ρ w j ⎞
⎠

1
ρ

1 1 v F n (1.355)

m

⎝ 1

1 − − − − v F n ≥ min

j

κ α j ,λ α j ( α j

)

κ α j ,λ α j ( α j

)

j = 1

Let

= μ α F n ,

α F n

GIFPWAF w (α 1 ,α 2 ,...,α n ) = α F n v

then

v F n

S α F n

(1.356)

S α F n = μ α F n

− v α F n ≤ max

j

μ F n − min

j

=

κ α j ,λ α j ( α j

)

κ α j ,λ α j ( α j

)

v F n

S

α F n
(1.357)

S α F n = μ α F n

− ≥ μ F n − =

v α F n min

j

max
j

κ α j ,λ α j ( α j

)

κ α j ,λ α j ( α j

)