Information Technology Reference
In-Depth Information
where
⎧
⎨
k
k
K
∗
)
μ
k
i
,
l
j
,ν
k
i
,
l
j
,
if
k
i
,α
i
,β
i
∈
N
ρ
1
,σ
1
(
l
l
L
∗
)
and
l
j
,α
j
,β
j
∈
N
ρ
2
,σ
2
(
and
μ
k
i
,
l
j
≥
ρ
3
&
ν
k
i
,
l
j
≤
σ
3
ϕ
k
i
,
l
j
,ψ
k
i
,
l
j
=
,
⎩
k
k
K
∗
)
0
,
1
,
if
k
i
,α
i
,β
i
∈
N
ρ
1
,σ
1
(
l
l
L
∗
)
and
l
j
,α
j
,β
j
∈
N
ρ
2
,σ
2
(
and
μ
k
i
,
l
j
<ρ
3
∨
ν
k
i
,
l
j
>σ
3
2.6 Aggregation Operations Over EIFIMs
Let the EIFIM
l
l
l
l
l
l
l
1
,
α
1
,β
1
...
l
j
,
α
j
,β
j
...
l
n
,
α
n
,β
n
k
k
k
1
,
α
1
,β
1
μ
k
1
,
l
1
,ν
k
1
,
l
1
...
μ
k
1
,
l
j
,ν
k
1
,
l
j
...
μ
k
1
,
l
n
,ν
k
1
,
l
n
.
.
.
.
. . .
. . .
A
=
,
k
k
k
i
,
α
i
,β
i
μ
k
i
,
l
1
,ν
k
i
,
l
1
...
μ
k
i
,
l
j
,ν
k
i
,
l
j
...
μ
k
i
,
l
n
,ν
k
i
,
l
n
.
.
.
.
. . .
. . .
m
,β
m
μ
k
m
,
l
1
,ν
k
m
,
l
1
...
μ
k
m
,
l
j
,ν
k
m
,
l
j
...
μ
k
m
,
l
n
,ν
k
m
,
l
n
k
m
,
α
be given and let
k
0
∈
L
be two fixed indices.
Now, we introduce the following 18 operations over it.
K
and
l
0
∈
(max,max)-row-aggregation
ρ
(
max
,
max
)
(
A
,
k
0
)
l
l
l
1
,
α
1
,β
1
...
=
k
k
k
0
,
max
m
α
i
,
min
m
β
i
max
m
μ
k
i
,
l
1
,
min
m
ν
k
i
,
l
1
...
1
≤
i
≤
1
≤
i
≤
1
≤
i
≤
1
≤
i
≤
l
n
,β
n
...
l
n
,
α
m
ν
k
i
,
l
n
,
...
max
1
m
μ
k
i
,
l
n
,
min
≤
i
≤
1
≤
i
≤
(max,ave)-row-aggregation
ρ
(
max
,
max
)
(
A
,
k
0
)
l
l
l
1
,
α
1
,β
1
...
i
=
1
μ
k
i
,
l
1
,
m
i
=
1
ν
k
i
,
l
1
...
m
=
k
k
1
m
1
m
k
0
,
max
1
m
α
i
,
min
m
β
i
≤
i
≤
1
≤
i
≤
Search WWH ::
Custom Search