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T
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CC B
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SA
li
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.
C
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r
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s
p
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A
uth
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r
:
Sli
m
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ass
in
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ab
o
r
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y
o
f
SATI
T
,
Dep
ar
t
m
en
t o
f
E
lectr
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E
n
g
in
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r
i
n
g
,
Facu
lty
o
f
Scien
ce
an
d
T
ec
h
n
o
lo
g
y
,
Ab
b
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L
ag
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r
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Un
i
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s
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f
Kh
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ch
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4
0
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0
4
,
Alg
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m
ail:
s
lim
an
i.h
ass
in
a@
u
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-
k
h
en
ch
ela.
d
z
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
r
ap
id
ad
v
a
n
ce
m
en
t
o
f
c
o
n
tem
p
o
r
ar
y
tech
n
o
lo
g
y
h
as
p
o
s
itio
n
ed
s
o
lar
en
er
g
y
as
a
lead
er
in
g
lo
b
al
r
e
n
ewa
b
le
p
o
wer
g
en
er
atio
n
.
[
1
]
,
[
2
]
.
T
h
is
wo
r
ld
wid
e
g
r
o
wth
is
m
o
s
tly
ascr
i
b
ed
to
th
e
ess
en
tial
f
u
n
ctio
n
o
f
s
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lar
en
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g
y
in
r
ed
u
cin
g
p
o
llu
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n
a
n
d
less
en
in
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th
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d
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im
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n
tal
im
p
ac
ts
o
f
en
v
ir
o
n
m
en
tal
d
eg
r
ad
atio
n
.
[
3
]
,
as
well
a
s
th
e
co
n
tin
u
o
u
s
d
ep
letio
n
o
f
f
o
s
s
il
f
u
el
r
eser
v
es,
wh
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h
as
a
m
p
lifie
d
th
e
g
lo
b
al
d
em
an
d
f
o
r
s
u
s
tain
ab
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alter
n
ativ
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Am
o
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g
t
h
e
m
o
s
t
p
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o
m
is
in
g
tech
n
o
lo
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p
h
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to
v
o
ltaic
(
PV)
s
y
s
tem
s
s
tan
d
o
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t
d
u
e
to
th
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v
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m
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tal
b
en
ef
its
,
s
u
s
tain
ab
ilit
y
,
an
d
s
af
ety
[
4
]
.
Ho
wev
er
,
s
ev
er
al
s
tu
d
ies
[
5
]
,
[
6
]
h
av
e
r
ep
o
r
ted
t
h
at
th
ese
s
y
s
tem
s
ar
e
s
u
s
ce
p
tib
le
to
s
u
d
d
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n
f
au
lts
th
at
m
ay
r
esu
lt
in
s
ig
n
if
ican
t
en
er
g
y
lo
s
s
es
an
d
r
ed
u
ce
d
co
m
p
o
n
en
t
life
s
p
an
.
T
h
is
u
n
d
er
s
co
r
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th
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n
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ed
f
o
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p
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is
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an
d
r
ap
id
d
e
f
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id
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tific
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to
en
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r
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tim
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p
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f
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m
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a
n
d
m
in
im
ize
m
ai
n
ten
an
ce
e
x
p
en
s
es.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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&
C
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I
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N:
2088
-
8
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f
a
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lt d
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d
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ith
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(
S
lima
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in
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5287
Nu
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m
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f
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ties
,
s
u
c
h
as
s
t
atis
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tec
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[
7
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an
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ea
r
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.
Ne
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m
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d
s
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b
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ti
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atte
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d
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b
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t
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[
9
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,
[
1
0
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.
F
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J
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.
[
1
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p
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At
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r
a
m
e
te
r
s
o
f
p
h
o
to
v
o
lta
ic
a
d
a
p
ti
v
e
g
u
i
d
e
d
d
i
f
f
e
r
e
n
ti
al
ev
o
l
u
t
i
o
n
al
g
o
r
it
h
m
(
AG
DE
)
m
o
d
e
ls
.
Fu
r
th
e
r
m
o
r
e
,
al
g
o
r
it
h
m
s
s
u
c
h
as
t
h
e
ar
t
if
ici
al
h
u
m
m
i
n
g
b
ir
d
al
g
o
r
it
h
m
(
AHA
)
[
1
3
]
a
n
d
m
o
d
if
ie
d
s
o
cia
l
n
et
wo
r
k
s
ea
r
c
h
al
g
o
r
it
h
m
c
o
m
b
i
n
e
d
wit
h
t
h
e
s
e
ca
n
t
m
et
h
o
d
(
MSNS
-
S
E
C
)
[
1
4
]
,
al
o
n
g
w
it
h
s
e
v
e
r
a
l
v
a
r
i
an
ts
o
f
p
a
r
ti
cle
s
w
ar
m
o
p
t
im
i
za
ti
o
n
(
P
SO
)
,
h
a
v
e
d
e
m
o
n
s
tr
ate
d
r
em
ar
k
a
b
l
e
o
p
ti
m
iz
ati
o
n
ca
p
ab
ilit
ies
a
n
d
r
es
u
lts
[
1
5
]
.
Ad
d
itio
n
al
d
ev
elo
p
m
en
ts
in
c
lu
d
e
an
ANFI
S
m
o
d
el
in
teg
r
ated
with
th
e
PS
O
alg
o
r
ith
m
,
wh
ich
ef
f
ec
tiv
ely
r
ed
u
ce
d
t
o
tal
h
ar
m
o
n
ic
d
is
to
r
tio
n
(
T
HD)
in
a
UPS
s
y
s
tem
p
o
wer
ed
b
y
L
iF
ePO₄
b
atter
ies
[
1
6
]
.
Mo
r
eo
v
er
,
th
e
tr
ee
s
ee
d
o
p
tim
izatio
n
(
T
SO)
tech
n
iq
u
e
d
em
o
n
s
tr
ates
a
n
o
tab
le
s
u
p
er
io
r
ity
o
v
er
m
u
ltip
le
m
eth
o
d
s
f
o
r
r
esu
lt
ac
c
u
r
ac
y
a
n
d
c
o
n
v
e
r
g
en
ce
s
p
ee
d
.
[
1
7
]
.
Hy
b
r
id
m
o
d
els,
s
u
ch
as
d
u
n
g
b
ee
tle
o
p
tim
izatio
n
alg
o
r
ith
m
co
m
b
in
ed
with
Fick
’
s
law
o
f
d
if
f
u
s
io
n
alg
o
r
ith
m
d
u
n
g
b
ee
tle
o
p
tim
izatio
n
alg
o
r
ith
m
co
m
b
in
e
d
with
F
ick
’
s
law
o
f
d
if
f
u
s
io
n
alg
o
r
ith
m
(
DB
FLA
)
[
1
8
]
,
QPSOL
[
1
9
]
,
an
d
w
h
ale
o
p
tim
izatio
n
alg
o
r
ith
m
-
a
r
tific
ial
n
eu
r
al
n
et
wo
r
k
(
W
OA
-
ANN
)
[
2
0
]
,
h
a
v
e
also
ac
h
iev
ed
o
u
ts
tan
d
in
g
p
er
f
o
r
m
a
n
ce
in
f
au
lt
class
if
icatio
n
an
d
im
p
r
o
v
in
g
d
iag
n
o
s
tic
ac
cu
r
ac
y
.
I
n
th
is
co
n
te
x
t,
th
e
g
r
ey
wo
lf
o
p
tim
izer
(
GW
O)
h
as
e
m
er
g
ed
as
o
n
e
o
f
th
e
m
o
s
t
ef
f
icien
t
m
etah
eu
r
is
tic
m
eth
o
d
s
,
b
o
th
i
n
its
o
r
ig
in
al
f
o
r
m
an
d
th
r
o
u
g
h
its
v
ar
io
u
s
m
o
d
if
ied
an
d
h
y
b
r
id
v
ar
ian
ts
,
o
win
g
to
its
h
ig
h
p
er
f
o
r
m
an
ce
in
p
h
o
to
v
o
ltaic
s
y
s
tem
ap
p
licatio
n
s
;
t
h
ese
ad
v
an
ce
m
en
ts
h
av
e
co
n
tr
ib
u
ted
to
f
aster
d
y
n
am
ic
r
esp
o
n
s
e,
r
ed
u
ce
d
e
n
er
g
y
lo
s
s
es,
an
d
im
p
r
o
v
e
d
v
o
l
tag
e
s
tab
ilit
y
u
n
d
er
v
ar
iab
le
o
p
er
atin
g
co
n
d
itio
n
s
[2
1
]
–
[3
1
]
.
Desp
ite
th
e
p
r
o
v
e
n
ef
f
icien
cy
o
f
v
ar
i
o
u
s
GW
O
v
ar
ian
ts
in
n
u
m
er
o
u
s
o
p
ti
m
izatio
n
task
s
,
th
eir
b
lack
-
b
o
x
n
atu
r
e
lim
its
in
ter
p
r
etab
ilit
y
an
d
tr
ac
e
ab
ilit
y
,
k
ey
r
eq
u
ir
em
en
ts
in
s
en
s
itiv
e
f
ield
s
s
u
ch
as
p
h
o
to
v
o
ltaic
s
y
s
tem
s
.
T
o
o
v
er
co
m
e
th
is
lim
itatio
n
,
th
e
d
iv
er
s
if
ied
g
r
ey
wo
l
f
o
p
tim
izer
alg
o
r
ith
m
(
DGWOA)
h
as
b
ee
n
in
tr
o
d
u
ce
d
.
B
y
in
te
g
r
atin
g
c
o
o
p
er
ati
v
e
s
ea
r
ch
s
t
r
ateg
ies
with
ex
p
lain
ab
le
AI
(
XAI
)
tech
n
i
q
u
es,
DGWOA
en
h
an
ce
s
tr
an
s
p
ar
en
cy
wh
ile
p
r
eser
v
in
g
h
ig
h
class
if
icatio
n
ac
cu
r
ac
y
.
I
ts
h
y
b
r
id
f
r
am
ewo
r
k
en
a
b
les
th
e
g
en
er
ati
o
n
o
f
ex
p
licit
d
ec
is
io
n
r
u
les
an
d
in
co
r
p
o
r
at
es
a
d
y
n
am
ic
co
n
tr
o
l
m
ec
h
an
is
m
to
b
alan
ce
ex
p
lo
r
atio
n
an
d
e
x
p
lo
itatio
n
,
e
n
s
u
r
in
g
ad
a
p
tab
ilit
y
an
d
im
p
r
o
v
ed
c
o
n
v
er
g
en
ce
.
T
h
e
n
ex
t
p
ar
ts
o
f
t
h
is
d
o
cu
m
en
t
ar
e
o
r
g
a
n
ized
as
o
u
tlin
ed
.
Me
th
o
d
o
lo
g
y
o
u
tlin
es
th
e
p
r
o
p
o
s
ed
tech
n
iq
u
e,
in
clu
d
i
n
g
th
e
class
if
icatio
n
task
,
th
e
e
r
r
o
r
ca
te
g
o
r
ies
co
n
s
id
er
e
d
,
a
n
d
th
e
d
a
tasets
u
tili
ze
d
.
T
h
e
ex
p
er
im
en
tal
r
esu
lts
s
ec
tio
n
p
r
esen
ts
a
co
m
p
r
eh
en
s
iv
e
ev
alu
atio
n
an
d
co
m
p
ar
ativ
e
an
aly
s
is
wi
th
ex
is
tin
g
m
o
d
els.
Fin
ally
,
th
e
r
esear
c
h
en
d
s
with
a
s
y
n
th
esis
o
f
th
e
m
ain
r
esu
lts
,
h
ig
h
lig
h
tin
g
th
e
m
o
d
el’
s
im
p
r
o
v
e
d
r
o
b
u
s
tn
ess
,
r
eliab
ilit
y
,
an
d
s
u
itab
ilit
y
f
o
r
r
ea
l w
o
r
ld
PV sy
s
tem
ap
p
licatio
n
s
.
2.
M
E
T
H
O
D
2
.
1
.
Dis
cr
et
e
g
re
y
wo
lf
o
ptim
iza
t
io
n
(
DG
WO
A
)
T
h
is
r
esear
ch
s
tu
d
y
p
r
esen
ts
th
e
DGW
OA,
a
n
o
v
el
ad
ap
tatio
n
o
f
th
e
o
r
ig
in
al
tech
n
iq
u
e
m
o
ld
ed
GW
O
b
y
th
e
s
o
cial
h
ier
ar
c
h
y
a
n
d
h
u
n
tin
g
b
eh
av
io
r
s
o
f
wo
lv
es.
I
n
teg
r
ate
d
with
e
x
p
lain
ab
le
a
r
tific
ial
in
tellig
en
ce
tech
n
iq
u
es,
DGWOA
f
ac
ilit
ate
s
th
e
g
en
er
at
io
n
o
f
in
ter
p
r
etab
le
class
if
icatio
n
r
u
les,
th
e
r
eb
y
en
h
an
cin
g
th
e
tr
an
s
p
ar
e
n
cy
an
d
r
eliab
ilit
y
o
f
d
ec
is
io
n
-
m
ak
in
g
.
Fig
u
r
e
1
s
h
o
ws
th
e
s
tr
u
ctu
r
e
o
f
th
e
DGWOA
-
b
ased
s
y
s
tem
f
o
r
d
iag
n
o
s
in
g
p
h
o
t
o
v
o
ltaic
(
PV)
f
au
lts
.
T
h
is
s
y
s
tem
en
h
an
ce
s
o
v
e
r
all
ef
f
icien
cy
an
d
ac
ce
ler
ates
s
o
lu
tio
n
c
o
n
v
er
g
e
n
ce
wh
en
d
ea
lin
g
with
co
m
p
l
ex
o
p
tim
izatio
n
p
r
o
b
lem
s
.
Fig
u
r
e
2
.
T
h
e
o
v
e
r
all
s
tr
u
ctu
r
e
o
f
t
h
e
p
r
o
p
o
s
ed
m
eth
o
d
is
b
ased
o
n
DGWOA
.
Fig
u
r
e
1
.
Stru
ctu
r
e
o
f
th
e
DG
W
OA
-
b
ased
s
y
s
tem
f
o
r
d
iag
n
o
s
in
g
PV f
au
lts
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
6
,
Decem
b
e
r
20
25
:
5
2
8
6
-
5
2
9
6
5288
Fig
u
r
e
2
.
T
h
e
p
r
o
p
o
s
ed
m
eth
o
d
DGWO
A
Alg
o
r
ith
m
1
r
e
p
r
esen
ts
th
e
p
r
ac
tical
im
p
lem
en
tatio
n
o
f
a
h
y
b
r
id
f
r
am
ewo
r
k
th
at
co
m
b
i
n
es
th
e
GW
O
alg
o
r
ith
m
with
ex
p
lain
ab
le
AI
(
XAI
)
tech
n
iq
u
es.
I
t
d
em
o
n
s
t
r
ates
h
o
w
th
is
in
teg
r
atio
n
en
ab
les
ac
cu
r
ate
f
au
lt
d
iag
n
o
s
is
in
p
h
o
to
v
o
ltaic
s
y
s
tem
s
wh
ile
en
s
u
r
in
g
th
e
lev
el
o
f
in
t
er
p
r
etab
ilit
y
r
eq
u
ir
e
d
f
o
r
r
ea
l
wo
r
ld
o
p
e
r
atin
g
en
v
ir
o
n
m
en
ts
.
Alg
o
r
ith
m
1
.
DGWOA
–
a
d
is
cr
ete
g
r
ey
w
o
lf
o
p
tim
izer
f
o
r
r
u
le
-
b
ased
class
if
icatio
n
I
np
ut
p
a
ra
m
et
er
s
:
D_
tr
ain
: T
r
ain
in
g
d
ataset
u
s
ed
f
o
r
r
u
le
in
d
u
ctio
n
D_
test
: T
esti
n
g
d
ataset
u
s
ed
f
o
r
m
o
d
el
ev
alu
atio
n
W
: T
o
tal
n
u
m
b
er
o
f
s
ea
r
ch
a
g
en
ts
(
wo
lv
es)
Ma
x
_
iter
: M
ax
im
u
m
n
u
m
b
er
o
f
o
p
tim
izatio
n
iter
atio
n
s
p
er
r
u
le
Min
_
in
s
tan
ce
: M
in
im
u
m
n
u
m
b
er
o
f
u
n
co
v
er
ed
tr
ain
in
g
in
s
tan
ce
s
to
ex
tr
ac
t a
r
u
le
O
utput
:
A
s
et
o
f
class
if
icatio
n
r
u
les f
o
r
ea
ch
tar
g
et
class
Per
f
o
r
m
an
ce
m
etr
ics:
Acc
u
r
ac
y
,
Pre
cisi
o
n
,
T
P,
FP
,
T
N,
FN
M
et
ho
do
lo
g
ica
l
f
ra
m
ew
o
rk
:
A
.
I
nitia
liza
t
io
n
ph
a
s
e
I
n
itialize
th
e
alg
o
r
ith
m
p
ar
am
eter
s
: W,
Ma
x
_
iter
,
Min
_
in
s
tan
ce
Star
t e
x
ec
u
tio
n
tim
er
Def
in
e
em
p
ty
r
u
lesets
: Ru
lese
t_
C
1
,
R
u
leset_
C
2
,
.
.
.
,
R
u
leset_
C
n
B
.
Rule
ex
t
ra
ct
io
n pha
s
e
Fo
r
ea
ch
class
C
i
∈
{C1
,
C
2
,
.
.
.
,
C
n
}:
Par
titi
o
n
D_
tr
ain
in
to
:
D_
p
o
s
: I
n
s
tan
ce
s
o
f
class
C
i
D_
n
eg
: I
n
s
tan
ce
s
n
o
t b
elo
n
g
in
g
to
C
i
W
h
ile
|
D_
p
o
s
|
>
Min
_
in
s
tan
ce
:
R
an
d
o
m
ly
in
itialize
W
wo
lv
es (
ca
n
d
id
ate
r
u
les)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
E
xp
la
in
a
b
le
f
a
u
lt d
ia
g
n
o
s
is
u
s
in
g
d
is
crete
g
r
ey
w
o
lf
o
p
timiz
a
tio
n
a
lg
o
r
ith
m
fo
r
…
(
S
lima
n
i H
a
s
s
in
a
)
5289
Fo
r
ea
ch
iter
atio
n
t =
1
to
Ma
x
_
iter
:
E
v
alu
ate
th
e
f
itn
ess
o
f
ea
c
h
w
o
lf
u
s
in
g
th
e
d
ef
in
e
d
f
itn
ess
f
u
n
ctio
n
s
(
E
q
u
atio
n
s
1
an
d
2
)
Select
th
e
to
p
th
r
ee
wo
lv
es a
s
Alp
h
a
(
b
est),
B
eta
(
s
ec
o
n
d
-
b
e
s
t)
,
an
d
Gam
m
a
(
t
h
ir
d
-
b
est)
Up
d
ate
p
o
s
itio
n
s
o
f
t
h
e
r
em
ai
n
in
g
wo
lv
es u
s
in
g
th
e
DGWO
A
s
tr
ateg
y
Af
ter
Ma
x
_
iter
,
s
et
th
e
Alp
h
a
wo
lf
'
s
v
ec
to
r
as a
n
ew
r
u
le
Ap
p
ly
th
e
n
ew
r
u
le
o
n
th
e
tr
ai
n
in
g
s
et
D_
tr
ain
R
em
o
v
e
co
v
er
e
d
in
s
tan
ce
s
f
r
o
m
D_
tr
ain
Ad
d
th
e
n
ew
r
u
le
to
R
u
leset_
C
i
C
.
T
esting
ph
a
s
e
Ap
p
ly
th
e
e
x
tr
ac
ted
r
u
leset o
n
th
e
test
d
ataset
D_
test
Fo
r
ea
ch
class
C
i:
C
o
m
p
u
te
co
n
f
u
s
io
n
m
atr
i
x
: T
P,
FP
,
T
N,
FN
C
alcu
late
p
er
f
o
r
m
an
ce
m
etr
ics:
Acc
u
r
ac
y
,
Pre
cisi
o
n
D
.
Ag
g
re
g
a
t
io
n
a
nd
re
po
rt
ing
C
o
m
b
in
e
r
esu
lts
f
o
r
all
class
es
R
ep
o
r
t f
in
al
class
if
icatio
n
p
er
f
o
r
m
an
ce
m
et
r
ics an
d
r
u
n
tim
e
2
.
2
.
T
he
da
t
a
s
et
T
h
is
s
tu
d
y
u
tili
ze
d
a
d
atase
t
av
ailab
le
o
n
th
e
Ka
g
g
le
p
latf
o
r
m
,
wh
ich
r
ep
r
esen
ts
o
p
er
atio
n
al
m
ea
s
u
r
em
en
ts
o
f
a
p
h
o
to
v
o
ltaic
s
y
s
tem
co
llected
f
r
o
m
a
s
im
u
lated
2
5
0
k
W
s
o
lar
f
ar
m
,
f
o
cu
s
in
g
o
n
d
etec
tin
g
m
u
ltip
le
ty
p
es
o
f
f
au
lts
(
F1
,
F2
,
an
d
F3
)
alo
n
g
s
id
e
th
e
n
o
r
m
al
o
p
er
atin
g
s
tate
(
F0
)
.
I
t
in
clu
d
es
s
am
p
led
m
ea
s
u
r
em
en
ts
o
f
en
v
i
r
o
n
m
e
n
tal
f
ac
to
r
s
,
in
clu
d
in
g
tem
p
er
atu
r
e,
s
u
n
ir
r
ad
ia
n
ce
,
a
n
d
f
a
u
lt
r
esis
tan
ce
,
with
ess
en
tial e
lectr
ical
v
ar
iab
les,
i
n
clu
d
in
g
cu
r
r
e
n
t,
v
o
ltag
e,
an
d
p
o
we
r
[
3
2
]
.
2
.
3
.
Rule
g
ener
a
t
i
o
n a
nd
f
it
nes
s
ev
a
lua
t
io
n
T
h
e
p
r
o
p
o
s
ed
p
r
ed
ictio
n
an
d
d
iag
n
o
s
is
ap
p
r
o
ac
h
is
b
ased
o
n
e
x
tr
ac
tin
g
class
if
icatio
n
r
u
les
th
at
d
ef
in
e
s
y
s
tem
o
p
er
atio
n
al
s
t
ates
th
r
o
u
g
h
s
tr
u
ct
u
r
ed
lo
g
ic
al
co
n
d
itio
n
s
,
en
a
b
lin
g
th
eir
ca
teg
o
r
izatio
n
in
t
o
p
r
ed
ef
in
e
d
class
es.
T
h
e
r
u
le
g
en
er
atio
n
p
r
o
ce
s
s
is
d
r
iv
en
b
y
a
r
elev
an
ce
f
u
n
ctio
n
g
r
o
u
n
d
ed
in
th
e
s
u
p
p
o
r
t
m
etr
ic
[
3
3
]
,
[
3
4
]
as
in
(
1
)
;
wh
ich
ev
alu
ates
ea
c
h
r
u
le
b
ase
d
o
n
th
e
t
o
tal
n
u
m
b
er
o
f
in
s
tan
ce
s
(
T
I
)
,
co
r
r
ec
tly
co
v
er
ed
ca
s
es
(
I
C
C
)
,
an
d
in
co
r
r
ec
tly
co
v
er
e
d
ca
s
es
(
I
NC
C
)
as
in
(
2
)
.
Fig
u
r
e
3
illu
s
tr
ates
th
e
m
eth
o
d
o
lo
g
ical
f
r
am
ewo
r
k
an
iter
ativ
e
r
e
f
in
e
m
en
t
cy
cle
to
im
p
r
o
v
e
class
if
icatio
n
ac
cu
r
ac
y
an
d
en
s
u
r
e
d
ia
g
n
o
s
tic
r
eliab
ilit
y
.
Fig
u
r
e
3
.
Flo
wch
ar
t
o
f
th
e
p
r
o
p
o
s
ed
r
u
le
-
b
ased
f
au
lt
d
iag
n
o
s
is
ap
p
r
o
ac
h
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
6
,
Decem
b
e
r
20
25
:
5
2
8
6
-
5
2
9
6
5290
=
(
1
)
=
(
−
)
∗
(
+
)
(
2
)
Fo
r
m
u
la
f
o
r
class
if
icatio
n
r
u
le
s
:
3.
E
XP
E
R
I
M
E
N
T
A
L
3
.
1
.
DG
WO
A
ev
a
lua
t
io
n
T
h
e
DGWOA
alg
o
r
ith
m
was
ex
ec
u
ted
m
u
ltip
le
tim
es
o
n
p
h
o
to
v
o
ltaic
(
PV)
s
y
s
tem
d
ata
b
y
v
ar
y
i
n
g
th
e
n
u
m
b
er
o
f
wo
lv
es
an
d
iter
atio
n
s
,
with
au
to
m
atica
lly
g
en
er
ated
s
ee
d
v
alu
es
in
ea
ch
r
u
n
.
As
p
r
esen
ted
in
T
ab
le
1
,
th
e
b
est
p
er
f
o
r
m
an
c
e
was
ac
h
iev
ed
with
1
1
0
w
o
lv
es
an
d
1
0
iter
atio
n
s
,
y
ield
i
n
g
a
class
if
icatio
n
ac
cu
r
ac
y
o
f
0
.
9
9
an
d
a
p
r
e
cisi
o
n
o
f
1
.
0
0
with
in
an
ex
ec
u
tio
n
tim
e
o
f
less
th
an
6
m
in
u
tes.
I
n
cr
ea
s
in
g
th
e
n
u
m
b
er
o
f
wo
l
v
es
b
ey
o
n
d
th
is
co
n
f
ig
u
r
atio
n
y
ield
ed
n
o
f
u
r
t
h
er
im
p
r
o
v
em
en
ts
an
d
r
esu
lte
d
in
a
s
lig
h
t
d
ec
lin
e
in
ef
f
icien
cy
.
T
h
ese
f
in
d
in
g
s
h
ig
h
lig
h
t
th
e
im
p
o
r
tan
ce
o
f
i
d
en
tify
in
g
an
o
p
tim
al
co
n
f
ig
u
r
atio
n
th
at
s
tr
ik
es
a
b
alan
ce
am
o
n
g
class
if
icatio
n
a
cc
u
r
ac
y
,
c
o
m
p
u
tatio
n
al
ex
p
e
n
s
e,
an
d
s
ea
r
ch
ef
f
icac
y
.
T
ab
le
1
.
DGWOA
p
er
f
o
r
m
a
n
c
e
u
n
d
er
v
ar
y
in
g
n
u
m
b
e
r
s
o
f
w
o
lv
es a
n
d
i
ter
atio
n
s
N
u
mb
e
r
o
f
w
o
l
v
e
s
N
u
mb
e
r
o
f
i
t
e
r
a
t
i
o
n
s
A
c
c
u
r
a
c
y
P
r
e
c
i
s
i
o
n
20
5
0
.
8
1
0
.
7
5
50
8
0
.
8
1
0
.
7
5
1
1
0
10
0
.
9
9
1
.
0
0
1
2
0
15
0
.
7
6
0
.
6
2
1
3
5
25
0
.
8
1
0
.
7
5
1
8
0
30
0
.
7
8
0
.
6
5
2
0
0
50
0
.
8
2
0
.
7
0
3
.
2
.
Rule
s
et
g
ener
a
t
io
n
T
ab
le
2
p
r
esen
ts
th
e
class
if
ica
tio
n
r
u
les
g
en
er
ated
b
y
th
e
D
GW
OA
a
lg
o
r
ith
m
,
y
ield
in
g
f
o
u
r
d
is
tin
ct
r
u
les:
o
n
e
f
o
r
th
e
n
o
r
m
al
co
n
d
itio
n
(
F0
–
C
lass
1
)
an
d
th
r
ee
f
o
r
f
a
u
lt
s
ce
n
ar
io
s
(
F1
,
F2
,
an
d
F3
–
C
lass
es
2
,
3
,
an
d
4
)
.
W
h
ile
s
o
m
e
r
u
les
ac
h
iev
ed
h
ig
h
class
if
icatio
n
ac
cu
r
ac
y
an
d
s
u
b
s
tan
tial
d
ata
co
v
er
ag
e,
r
ea
ch
in
g
b
en
ch
m
ar
k
lev
el
p
er
f
o
r
m
an
ce
,
o
th
er
s
s
h
o
wed
r
ed
u
ce
d
ac
cu
r
ac
y
an
d
l
o
wer
co
v
er
ag
e,
in
d
ic
atin
g
v
ar
iab
ilit
y
in
g
en
er
aliza
tio
n
.
R
u
le
co
v
er
ag
e
r
an
g
ed
f
r
o
m
1
6
%
to
3
4
%
(
9
4
to
1
9
8
in
s
tan
ce
s
)
,
h
ig
h
lig
h
tin
g
ar
ea
s
f
o
r
p
o
te
n
tial
r
ef
in
em
en
t
to
im
p
r
o
v
e
co
m
p
l
eten
ess
an
d
r
eliab
ilit
y
.
T
ab
le
3
p
r
esen
ts
t
h
e
tr
u
e
-
p
o
s
itiv
es
(
TP
)
,
f
alse
-
p
o
s
itiv
es
(
FP
)
,
tr
u
e
-
n
eg
ativ
es
(
TN
)
,
a
n
d
f
alse
-
n
eg
ativ
es
(
FN
)
v
al
u
es
p
er
class
,
an
d
T
ab
le
4
p
r
o
v
id
es
a
co
n
f
u
s
io
n
m
atr
ix
-
b
ased
p
e
r
f
o
r
m
an
ce
a
n
a
ly
s
is
,
en
ab
lin
g
a
d
etailed
e
v
alu
atio
n
ac
r
o
s
s
all
f
au
lt c
ateg
o
r
i
es.
T
ab
le
2
.
T
h
e
r
esu
ltin
g
r
u
les
R
u
l
e
#
G
e
n
e
r
a
t
e
d
r
u
l
e
s
C
l
a
s
s
N
u
mb
e
r
o
f
t
e
r
ms
N
u
mb
e
r
o
f
i
n
st
a
n
c
e
s
c
o
r
r
e
c
t
l
y
c
o
v
e
r
e
d
N
u
mb
e
r
o
f
i
n
st
a
n
c
e
s
n
o
t
c
o
r
r
e
c
t
l
y
c
o
v
e
r
e
d
R
u
l
e
's
a
c
c
u
r
a
c
y
0
1
I
f
r
a
n
g
e
1
i
n
r
a
n
g
e
(
0
.
0
0
1
9
3
)
-
(
0
.
1
0
6
9
)
a
n
d
r
a
n
g
e
3
i
n
r
a
n
g
e
>
(
0
)
t
h
e
n
N
o
r
mal
mo
d
e
(
F
0
)
C
l
a
s
s
1
2
9
4
/
1
0
0
0
16
%
0
2
I
f
r
a
n
g
e
1
i
n
r
a
n
g
e
(
0
.
1
0
6
9
)
-
(
5
.
3
1
4
1
)
a
n
d
r
a
n
g
e
3
i
n
r
a
n
g
e
>
(
0
)
t
h
e
n
D
e
f
a
u
l
t
1
(
F
1
)
C
l
a
s
s2
2
1
4
4
/
1
4
6
1
2
4
%
0
3
I
f
r
a
n
g
e
3
i
n
r
a
n
g
e
(
-
4
.
2
5
)
-
(
-
0
.
0
6
6
2
)
a
n
d
r
a
n
g
e
4
i
n
r
a
n
g
e
<
(
0
)
t
h
e
n
D
e
f
a
u
l
t
2
(
F
2
)
C
l
a
s
s3
2
1
4
3
/
1
4
4
0
2
4
%
04
I
f
r
a
n
g
e
4
i
n
r
a
n
g
e
>
(
0
.
0
6
2
1
)
t
h
e
n
D
e
f
a
u
l
t
3
(
F
3
)
C
l
a
s
s4
1
1
9
8
/
1
9
8
0
3
4
%
E
v
a
l
u
a
t
e
C
o
r
r
e
c
t
l
y
c
l
a
ss
i
f
i
e
d
i
n
st
a
n
c
e
s
=
9
6
o
u
t
o
f
9
7
.
9
6
M
o
d
e
l
a
c
c
u
r
a
c
y
=
0
.
9
9
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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5293
Fig
u
r
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7
.
Statis
tical
s
tab
ilit
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aly
s
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DGWOA
b
ased
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ce
4.
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is
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g
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ad
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ial
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ed
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eth
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ated
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s
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ata
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a
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o
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y
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er
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n
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o
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etize
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ate
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r
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e
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atin
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r
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ie
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g
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o
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r
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9
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r
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iv
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en
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m
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atio
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n
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h
e
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ir
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t in
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et
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ith
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ile
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ased
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e
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em
o
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ated
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p
ac
ity
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ate
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s
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ilit
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aly
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is
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ased
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f
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v
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r
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ir
m
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ith
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s
n
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m
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n
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iatio
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ased
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r
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d
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n
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r
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co
r
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f
f
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ly
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ig
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m
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ac
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m
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u
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ain
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w
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d
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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@y
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fr
.
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