Information Technology Reference
In-Depth Information
R6:
(a) If KL(Ci)
i
)
=
Un and KL(C
j
)
=
MKn, then KL(C
i
)
=
MKn with
µ
MKN
(
C
i
) = µ
MKN
C
j
∗ µ
D
C
j
,
C
i
(b) If KL(Ci)
i
)
=
Un and KL(C
j
)
=
Kn, then KL(C
i
)
=
Kn with
µ
KN
(
C
i
) = µ
KN
C
j
∗ µ
D
C
j
,
C
i
(c) If KL(Ci)
i
)
=
Un and KL(C
j
)
=
L, then KL(C
i
)
=
L with
µ
L
(
C
i
) = µ
L
C
j
∗ µ
D
C
j
,
C
i
(d) If KL(Ci)
i
)
=
Un and KL(C
j
)
=
A, then KL(C
i
)
=
A with
µ
A
(
C
i
) = µ
A
C
j
∗ µ
D
C
j
,
C
i
(e) If KL(Ci)
i
)
=
MKn and KL(C
j
)
=
Kn, then KL(C
i
)
=
Kn with
µ
KN
(
C
i
) = µ
KN
C
j
∗ µ
D
C
j
,
C
i
(f)
If KL(Ci)
i
)
=
MKn and KL(C
j
)
=
L, then KL(C
i
)
=
L with
µ
L
(
C
i
) = µ
L
C
j
∗ µ
D
C
j
,
C
i
(g) If KL(Ci)
i
)
=
MKn and KL(C
j
)
=
A, then KL(C
i
)
=
A with
µ
A
(
C
i
) = µ
A
C
j
∗ µ
D
C
j
,
C
i
(h) If KL(Ci)
i
)
=
Kn and KL(C
j
)
=
L, then KL(C
i
)
=
L with
µ
L
(
C
i
) = µ
L
C
j
∗ µ
D
C
j
,
C
i
(i)
If KL(Ci)
i
)
=
Kn and KL(C
j
)
=
A, then KL(C
i
)
=
A with
µ
A
(
C
i
) = µ
A
C
j
∗ µ
D
C
j
,
C
i
(j)
If KL(Ci)
i
)
=
L and KL(C
j
)
=
A, then KL(C
i
)
=
A with
µ
A
(
C
i
) = µ
A
C
j
∗ µ
D
C
j
,
C
i
•
Based on updates of the KL(Ci)
j
), the KL(C
i
) is deteriorated according to:
R7:
If KL(Ci)
i
)
=
A with
μ
A
(Ci)
=
1
, then it does not change.
R8:
The formula
X
I
=
1
−
µ
D
C
I
,
C
J
∗
X
I
+
MIN
[
µ
D
C
I
,
C
J
∗
X
I
,
µ
D
∗
X
J
]
, where x
i
and x
j
are the degree of success, which determine the
fuzzy sets that are active each time for Ci
i
and C
j
respectively, is used (for the
calculation of previous xi,
i
, the membership value of the upper active fuzzy
set is used). Then, using the new xi,
i
, the KL(C
i
) is determined, calculating the
membership functions.
C
I
,
C
J
•
Limitation
L1:
µ
Un
+ µ
MKn
+ µ
Kn
+ µ
L
+ µ
A
=
1.
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