Information Technology Reference
In-Depth Information
According to the proposition 6.1 the weighed segment of
T
-number
(
~
)
A
≡
a
,
a
,
a
L
a
,
is the segment:
1
2
R
1
1
[
]
A
,
A
,
A
=
a
−
a
,
A
=
a
+
a
.
1
2
1
1
L
2
2
R
6
6
~
~
Let us define an affinity measure for two
T
-numbers
with the weighed
A
,
B
[
]
[
]
A
1
,
A
B
1
,
B
segments
,
2
2
(
)
~
~
(
)
(
)
2
2
f
A
,
B
=
A
−
B
+
A
−
B
.
1
1
2
2
Let
~
⎛
⎞
Y
⎜
⎟
1
~
~
(
)
i
i
i
L
i
R
i
i
L
Y
=
⎜
...
⎟
,
Y
≡
y
,
y
,
y
,
y
,
y
−
y
≥
0
i
=
1
n
i
1
2
1
⎜
⎜
⎟
⎟
Y
⎝
⎠
n
be output
T
-numbers, and
~
⎛
⎞
X
1
⎜
⎟
j
~
~
(
)
i
j
ji
ji
ji
L
ji
R
ji
ji
L
X
=
⎜
...
⎟
,
X
≡
x
,
x
,
x
,
x
,
x
−
x
≥
0
j
=
1
m
,
i
=
1
n
j
1
2
1
⎜
⎜
⎟
⎟
n
j
X
⎝
⎠
be input
T
-numbers.
Relation between input and output data will be determined as
~
~
~
~
~
~
Y
=
a
+
a
X
+
...
+
a
m
X
,
0
1
1
m
(
)
~
j
j
L
j
R
a
≡
b
,
b
,
b
where
are unknown coefficients of a regression model.
Let us define the weighed segments, using the proposition 6.1:
,
j
=
0
m
j
1
1
⎡
⎤
i
i
L
i
i
R
y
−
y
,
y
+
y
,
i
=
1
n
⎢
⎣
⎥
⎦
1
2
6
6
~
. Let us denote the weighed segment of product of
for observable output data
~
numbers
and
j
~
,
j
=
1
m
,
i
=
0
n
with
i
j
[
]
(
)
(
)
1
j
j
L
j
R
2
j
j
L
j
R
θ
b
,
b
,
b
,
θ
b
,
b
,
b
~
~
~
~
i
j
i
j
a
X
a
X
j
j
~
(
)
Let us consider nonnegative
T
-number
,
and a
X
≡
x
,
x
,
x
L
x
,
x
−
x
≥
0
1
2
R
1
L
~
(
)
a
≡
b
,
b
L
b
,
triangular number
.
R
