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e
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se
m
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t
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a
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Tran
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o
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n
.
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su
lt
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ro
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a
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s to
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rt
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ri
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isio
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m
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w
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to
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tab
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ab
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rticle
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CC B
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SA
li
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se
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C
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s
p
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A
uth
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r
:
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Ku
m
ar
Pag
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ti
L
in
co
ln
Un
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r
s
ity
C
o
lleg
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Petalin
g
J
ay
a
4
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3
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1
,
Selan
g
o
r
Dar
u
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h
s
an
,
Ma
lay
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ail:
p
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f
.
s
ir
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h
@
lin
co
ln
.
ed
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.
m
y
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ir
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g
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g
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co
m
1.
I
NT
RO
D
UCT
I
O
N
Mo
d
er
n
elec
tr
ic
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r
id
s
ar
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er
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o
in
g
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ap
id
tr
an
s
f
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atio
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d
u
e
to
th
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cr
ea
s
in
g
in
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atio
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d
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atter
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s
,
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d
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ec
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tr
alize
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g
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.
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ese
d
ev
elo
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ts
in
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o
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ce
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ig
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if
ican
t
u
n
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ta
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ty
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ex
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ased
co
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tr
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f
o
r
m
ai
n
tain
in
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-
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tab
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[
1
]
-
[
3
]
.
As
a
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lt,
th
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is
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h
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ata
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ML
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n
d
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b
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I
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8
7
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2
F
ea
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tr
a
n
s
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tio
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tem
s
tates
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s
[
4
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,
[
5
]
.
T
h
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ap
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ac
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ticu
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[
6
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[
7
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Dee
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(
DL
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f
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r
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[
9
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.
Similar
ly
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ased
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n
tex
tu
al
in
f
o
r
m
atio
n
in
s
tr
u
ctu
r
e
d
tab
u
lar
d
ata
[
1
0
]
,
[
1
1
]
.
Desp
ite
th
ese
ad
v
an
ce
m
en
ts
,
s
ev
er
al
ch
allen
g
es
r
em
ai
n
.
M
an
y
ex
is
tin
g
m
o
d
els
f
ac
e
is
s
u
es
s
u
ch
as
lo
w
in
ter
p
r
etab
ilit
y
,
im
b
alan
c
ed
lear
n
in
g
o
u
tco
m
es,
an
d
p
o
o
r
ly
ca
lib
r
ated
p
r
o
b
ab
ilit
y
esti
m
ates,
all
o
f
wh
ich
ar
e
cr
itical
lim
itatio
n
s
in
h
ig
h
-
s
tak
es
g
r
id
co
n
tr
o
l
en
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ir
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n
m
e
n
ts
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n
ad
d
itio
n
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h
y
b
r
id
f
r
am
e
wo
r
k
s
th
at
c
o
m
b
in
e
th
e
s
tr
en
g
th
s
o
f
d
ee
p
r
ep
r
ese
n
tatio
n
lear
n
in
g
an
d
en
s
em
b
l
e
d
ec
is
io
n
m
o
d
els
ar
e
s
till
u
n
d
er
ex
p
lo
r
ed
in
g
r
id
s
tab
ilit
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ap
p
licatio
n
s
.
T
o
ad
d
r
ess
th
ese
g
ap
s
,
th
is
s
tu
d
y
p
r
o
p
o
s
es
an
d
ev
alu
ates
two
h
y
b
r
i
d
ar
ch
itectu
r
es
th
at
in
teg
r
ate
d
ee
p
f
ea
tu
r
e
tr
a
n
s
f
o
r
m
atio
n
with
e
n
s
em
b
le
lear
n
i
n
g
to
im
p
r
o
v
e
th
e
r
eliab
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o
f
b
in
ar
y
g
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s
tab
ilit
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class
if
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n
.
T
h
e
f
ir
s
t
ap
p
r
o
ac
h
em
p
l
o
y
s
an
au
to
e
n
co
d
e
r
-
b
ased
en
co
d
er
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o
u
p
le
d
with
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n
E
x
tr
e
m
e
Gr
ad
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t
B
o
o
s
tin
g
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XGBo
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s
t)
t
clas
s
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ie
r
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ile
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n
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ap
p
lies
T
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an
s
f
o
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m
er
f
o
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e
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en
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llo
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d
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th
e
s
am
e
g
r
ad
ien
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g
c
lass
if
ier
[
1
2
]
.
T
h
ese
h
y
b
r
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m
o
d
els
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e
s
y
s
tem
atica
lly
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le
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s
in
g
a
p
u
b
licly
av
ailab
l
e
g
r
id
s
tab
ilit
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d
ataset.
T
h
e
ev
alu
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n
co
n
s
id
er
s
n
o
t
o
n
ly
ac
c
u
r
ac
y
an
d
F1
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s
co
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t
also
class
b
alan
ce
,
in
ter
p
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etab
ilit
y
,
an
d
c
o
n
f
id
e
n
ce
ca
l
ib
r
atio
n
[
1
3
]
,
[
1
4
]
,
wh
ich
ar
e
k
e
y
m
etr
ics
alig
n
ed
with
r
ea
l
-
wo
r
l
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o
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ati
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n
al
n
ee
d
s
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h
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r
k
co
n
tr
ib
u
tes
to
war
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th
e
d
ev
elo
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m
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n
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s
m
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te
r
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e
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ML
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ased
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r
am
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k
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t
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g
e
n
er
atio
n
p
o
we
r
g
r
id
r
esil
ien
ce
[
1
5
]
.
2.
M
E
T
H
O
D
2
.
1
.
Da
t
a
s
et
d
escript
io
n
T
h
is
s
tu
d
y
u
s
es
th
e
p
u
b
licly
av
ailab
le
“
s
m
ar
t
g
r
id
s
tab
ilit
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”
d
ataset
f
r
o
m
Kag
g
le,
wh
ic
h
co
n
tain
s
6
0
,
0
0
0
r
ec
o
r
d
s
.
E
ac
h
r
ec
o
r
d
r
ep
r
esen
ts
an
o
p
er
atio
n
al
s
tate
o
f
an
elec
tr
ic
p
o
wer
g
r
i
d
with
1
2
co
n
tin
u
o
u
s
in
p
u
t
f
ea
tu
r
es g
r
o
u
p
ed
in
to
th
r
ee
lay
er
s
:
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Gen
er
atio
n
lay
er
:
f
o
u
r
in
ter
n
al
d
am
p
in
g
co
ef
f
icien
ts
(
τ
1
to
τ
4
)
-
T
r
an
s
m
is
s
io
n
lay
er
:
f
o
u
r
p
o
wer
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u
tp
u
t r
ea
d
in
g
s
(
p
1
t
o
p
4
)
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Dis
tr
ib
u
tio
n
lay
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:
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o
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r
p
h
ase
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g
le
in
d
icato
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s
(
g
1
to
g
4
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h
e
d
ataset
p
r
o
v
id
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g
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tp
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ts
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co
n
tin
u
o
u
s
s
tab
ilit
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in
d
ex
(
s
tab
)
an
d
a
ca
te
g
o
r
ical
lab
el
(
s
tab
f
)
in
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wh
eth
er
th
e
g
r
id
s
tate
is
"stab
le"
o
r
"u
n
s
tab
le
.
"
T
h
is
s
tu
d
y
f
o
cu
s
es
o
n
th
e
b
in
ar
y
class
if
icatio
n
task
u
s
in
g
s
t
ab
f
.
All
f
ea
tu
r
es
ar
e
co
n
tin
u
o
u
s
,
an
d
th
e
d
ataset
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n
tain
s
n
o
m
is
s
in
g
v
alu
es.
B
ef
o
r
e
tr
ain
in
g
,
in
p
u
t
f
ea
tu
r
es
wer
e
n
o
r
m
alize
d
u
s
in
g
s
tan
d
ar
d
s
ca
lin
g
.
T
h
e
d
ataset
co
v
er
s
d
i
v
er
s
e
g
r
i
d
co
n
d
itio
n
s
,
o
f
f
er
i
n
g
a
r
o
b
u
s
t
b
asis
f
o
r
ev
alu
atin
g
p
r
ed
ictiv
e
m
o
d
els [
1
6
]
,
[
1
7
]
.
Fig
u
r
e
1
illu
s
tr
ates
th
e
m
ap
p
in
g
o
f
th
e
g
en
e
r
atio
n
(
τ
1
–
τ
4
)
,
tr
an
s
m
is
s
io
n
(
p
1
–
p
4
)
,
a
n
d
d
i
s
tr
ib
u
tio
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(
g
1
–
g
4
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f
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tu
r
es to
th
eir
r
esp
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tiv
e
lay
er
s
in
th
e
elec
tr
ic
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r
id
,
lead
in
g
to
a
b
in
ar
y
s
tab
ilit
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o
u
tco
m
e.
Fig
u
r
e
1
.
Sch
em
atic
r
ep
r
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t
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n
o
f
th
e
d
ataset'
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g
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p
s
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2
.
T
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ab
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s
t
ed
class
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n
f
o
r
s
tab
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y
p
r
ed
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n
[
1
8
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
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1
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.
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t
[
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1
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.
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h
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Fig
u
r
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2
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2
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t
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Au
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th
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im
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v
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lear
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g
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f
icien
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[
2
2
]
.
2
.
3
.
1
.
F
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t
ure
e
x
t
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ct
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o
n us
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ng
a
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T
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in
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al
laten
t
s
p
ac
e.
T
h
is
p
r
o
ce
s
s
r
ed
u
ce
s
n
o
is
e
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d
r
e
d
u
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d
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p
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e
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at
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p
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ess
en
tial
ch
ar
ac
ter
is
tic
s
o
f
th
e
g
r
id
d
ata
[
2
3
]
,
[
2
4
]
.
T
h
e
m
o
d
el
is
o
p
tim
ized
b
y
m
in
im
izin
g
th
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r
ec
o
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tr
u
ctio
n
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,
as sh
o
wn
in
(
4
)
.
=
1
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‖
−
̂
‖
2
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4
)
Af
ter
tr
ain
in
g
,
th
e
d
ec
o
d
er
is
d
is
ca
r
d
ed
,
an
d
o
n
ly
th
e
e
n
co
d
er
is
r
etain
ed
to
g
en
er
ate
co
m
p
r
ess
ed
f
ea
tu
r
es
f
o
r
class
if
icatio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
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E
n
g
I
SS
N:
2252
-
8
7
9
2
F
ea
tu
r
e
tr
a
n
s
fo
r
ma
tio
n
w
ith
en
s
emb
le
lea
r
n
in
g
fo
r
p
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er g
r
id
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ta
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ilit
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S
ir
is
h
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u
ma
r
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a
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o
ti
)
301
2
.
3
.
2
.
Wo
rkf
lo
w
Du
r
in
g
tr
ain
in
g
,
th
e
a
u
to
en
c
o
d
er
lear
n
s
co
m
p
ac
t
f
ea
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r
e
r
e
p
r
esen
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s
f
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o
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t
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atr
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T
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ese
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ain
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a
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le
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er
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er
ates
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m
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ed
r
ep
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z′,
wh
i
ch
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ied
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s
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g
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ed
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o
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t
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o
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el
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h
is
h
y
b
r
id
ap
p
r
o
ac
h
im
p
r
o
v
es
p
r
ed
ictio
n
b
y
r
ed
u
cin
g
f
ea
tu
r
e
n
o
is
e
an
d
f
o
cu
s
in
g
o
n
m
ea
n
in
g
f
u
l
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atter
n
s
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ile
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etain
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g
t
h
e
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ter
p
r
eta
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ilit
y
an
d
e
f
f
icien
cy
o
f
XGBo
o
s
t
[
2
5
]
-
[
2
7
]
.
T
h
e
o
v
er
all
p
r
o
ce
s
s
is
s
h
o
wn
in
Fig
u
r
e
3
.
Fig
u
r
e
3
.
Ar
c
h
itectu
r
e
o
f
th
e
AE
-
XGBo
o
s
t h
y
b
r
id
m
o
d
el
2
.
4
.
XG
B
o
o
s
t
c
l
a
s
s
if
ier
XGBo
o
s
t
is
a
g
r
ad
ien
t
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b
o
o
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te
d
en
s
em
b
le
o
f
d
ec
is
io
n
tr
ee
s
,
wid
ely
r
ec
o
g
n
ized
f
o
r
its
s
ca
lab
ilit
y
an
d
in
ter
p
r
etab
ilit
y
.
I
n
th
is
s
tu
d
y
,
it
s
er
v
es
as
th
e
d
ec
is
io
n
lay
er
f
o
r
b
o
th
h
y
b
r
id
m
o
d
els
(
T
T
-
XGBo
o
s
t
an
d
AE
-
XGBo
o
s
t)
.
T
h
e
lear
n
in
g
p
r
o
ce
s
s
is
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ef
in
ed
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y
th
e
o
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jectiv
e
f
u
n
ctio
n
as sh
o
wn
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n
(
5
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.
ℒ
(
)
=
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(
y
i
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y
̂
i
(
t
−
1
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+
(
)
)
+
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(
)
n
i
=
1
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5
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W
h
er
e
ℓ
is
a
d
if
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er
en
tiab
le
lo
s
s
f
u
n
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e
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g
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ee
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p
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ated
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iv
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in
(
6
)
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̂
(
)
=
̂
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−
1
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(
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(
6
)
W
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er
e
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th
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lear
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in
g
r
ate
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tr
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ize.
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o
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u
m
m
ar
ize
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e
en
d
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to
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d
p
r
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ce
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s
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o
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ith
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1
o
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n
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ied
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k
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lo
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o
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th
e
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r
o
p
o
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ed
h
y
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id
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o
s
t
an
d
T
T
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o
s
t
m
o
d
els
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o
r
g
r
id
s
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ilit
y
p
r
ed
ictio
n
.
T
h
is
f
o
r
m
u
latio
n
is
ap
p
lied
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n
s
is
ten
tly
ac
r
o
s
s
b
o
th
h
y
b
r
id
m
o
d
els
to
en
s
u
r
e
a
u
n
if
ied
class
if
icatio
n
f
r
am
ewo
r
k
.
Alg
o
r
ith
m
1
.
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b
r
id
AE
-
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o
s
t a
n
d
T
T
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o
s
t
wo
r
k
f
l
o
w
f
o
r
g
r
id
s
tab
ilit
y
p
r
e
d
ictio
n
I
n
p
u
t:
s
m
ar
t g
r
id
d
ataset
(
1
2
f
ea
tu
r
es,
s
tab
ilit
y
lab
el)
Ou
tp
u
t:
p
r
ed
icted
s
tab
ilit
y
s
tate
(
s
tab
le/u
n
s
tab
le
)
1.
L
o
ad
an
d
n
o
r
m
alize
th
e
d
atase
t; sp
lit in
to
tr
ain
in
g
an
d
test
in
g
s
ets.
2.
Fo
r
AE
-
XGBo
o
s
t:
-
T
r
ain
Au
to
e
n
co
d
e
r
to
e
x
tr
ac
t c
o
m
p
r
ess
ed
f
ea
tu
r
es (
Z
_
AE
)
.
3.
Fo
r
T
T
-
XGBo
o
s
t:
-
Use T
ab
T
r
an
s
f
o
r
m
er
to
e
m
b
ed
f
ea
tu
r
es a
n
d
ap
p
l
y
atten
tio
n
to
o
b
tain
(
Z
_
T
T
)
.
4.
T
r
ain
XGBo
o
s
t c
lass
if
ier
u
s
in
g
Z
_
AE
an
d
Z
_
T
T
f
ea
tu
r
es se
p
ar
ately
.
5.
E
v
alu
ate
all
m
o
d
els
(
R
F,
L
ig
h
tGB
M,
AE
-
XGBo
o
s
t,
T
T
-
XGBo
o
s
t)
u
s
in
g
ac
cu
r
ac
y
,
F1
,
MCC
,
an
d
R
OC
-
AUC.
6.
C
o
m
p
ar
e
r
esu
lts
to
id
en
tify
th
e
m
o
s
t a
cc
u
r
ate
an
d
co
m
p
u
tatio
n
ally
ef
f
icien
t
m
o
d
el.
7.
Dep
lo
y
th
e
s
elec
ted
m
o
d
el
f
o
r
r
ea
l
-
tim
e
g
r
id
m
o
n
ito
r
in
g
a
n
d
d
ec
is
io
n
s
u
p
p
o
r
t.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
9
2
I
n
t J Ap
p
l Po
wer
E
n
g
,
Vo
l.
1
5
,
No
.
1
,
Ma
r
ch
20
2
6
:
298
-
3
0
7
302
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
p
r
o
p
o
s
ed
h
y
b
r
id
m
o
d
el
s
wer
e
co
m
p
ar
ed
with
wid
e
ly
u
s
ed
m
ac
h
in
e
lear
n
i
n
g
te
ch
n
iq
u
es.
Per
f
o
r
m
an
ce
was
ev
alu
ated
u
s
in
g
ac
cu
r
ac
y
,
p
r
ec
is
io
n
,
r
e
ca
ll,
an
d
F1
-
s
co
r
e,
as
s
h
o
wn
in
T
a
b
le
1
.
AE
-
XGBo
o
s
t
clea
r
ly
o
u
tp
er
f
o
r
m
s
all
o
th
er
m
o
d
els,
ac
h
iev
in
g
9
7
.
7
3
%
ac
cu
r
ac
y
with
ex
ce
llen
t
p
r
ec
is
io
n
,
r
ec
all,
an
d
F1
-
s
co
r
es
ac
r
o
s
s
b
o
t
h
cla
s
s
es.
L
ig
h
tGB
M
al
s
o
p
er
f
o
r
m
s
s
tr
o
n
g
ly
,
m
ain
tain
in
g
a
g
o
o
d
b
alan
ce
b
etwe
en
ac
cu
r
ac
y
an
d
in
ter
p
r
eta
b
ilit
y
.
I
n
co
n
tr
ast,
T
T
-
XGBo
o
s
t
r
ec
o
r
d
s
th
e
lo
west
ac
cu
r
ac
y
(
8
9
.
4
2
%)
an
d
s
tr
u
g
g
les
p
ar
ticu
lar
ly
with
u
n
s
tab
le
s
tates
(
C
la
s
s
1
)
,
r
ef
lecte
d
in
its
lo
wer
r
ec
all
an
d
F1
-
s
co
r
e.
T
o
g
ain
d
ee
p
er
in
s
ig
h
ts
,
co
m
p
o
s
ite
in
d
icato
r
s
s
u
ch
as
Ma
tth
ews
co
r
r
elatio
n
co
e
f
f
ici
en
t
(
MCC
)
,
b
alan
ce
d
ac
c
u
r
ac
y
,
an
d
R
OC
AU
C
wer
e
also
co
m
p
u
ted
(
T
a
b
le
2
)
.
AE
-
XGBo
o
s
t
ag
ain
lead
s
ac
r
o
s
s
all
th
r
ee
m
ea
s
u
r
es,
f
o
llo
wed
clo
s
ely
b
y
L
ig
h
tGB
M,
wh
ile
T
T
-
XGBo
o
s
t sh
o
ws we
ak
er
r
eliab
ilit
y
an
d
b
alan
ce
.
Fig
u
r
e
4
p
r
o
v
id
es
a
c
o
n
s
o
lid
a
ted
co
m
p
a
r
is
o
n
o
f
all
m
o
d
els
ac
r
o
s
s
k
ey
m
et
r
ics,
in
clu
d
in
g
v
alid
atio
n
ac
cu
r
ac
y
,
test
ac
cu
r
ac
y
,
p
r
e
cisi
o
n
,
r
ec
all,
F1
-
s
co
r
e,
an
d
R
O
C
AU
C
.
T
h
e
AE
-
XG
B
o
o
s
t
m
o
d
el
s
h
o
ws
co
n
s
is
ten
tly
s
u
p
er
io
r
p
er
f
o
r
m
an
ce
,
f
o
llo
we
d
clo
s
ely
b
y
L
i
g
h
tGB
M.
Me
an
wh
ile,
T
T
-
X
GB
o
o
s
t
lag
s
s
lig
h
tly
d
u
e
to
h
ig
h
er
s
en
s
itiv
ity
to
c
o
n
tin
u
o
u
s
f
ea
t
u
r
e
s
ca
lin
g
.
T
ab
le
1
.
Per
f
o
r
m
an
ce
m
etr
ics o
f
h
y
b
r
id
a
n
d
b
aselin
e
m
o
d
els
f
o
r
g
r
id
s
tab
ilit
y
p
r
e
d
ictio
n
M
o
d
e
l
V
a
l
i
d
a
t
i
o
n
a
c
c
u
r
a
c
y
Te
st
a
c
c
u
r
a
c
y
P
r
e
c
i
s
i
o
n
R
e
c
a
l
l
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-
s
c
o
r
e
C
l
a
s
s
0
C
l
a
s
s
1
C
l
a
s
s
0
C
l
a
s
s
1
C
l
a
s
s
0
C
l
a
s
s
1
R
a
n
d
o
m
f
o
r
e
s
t
0
.
9
4
4
6
0
.
9
3
8
6
0
.
9
4
0
.
9
3
0
.
9
6
0
.
9
0
.
9
5
0
.
9
1
Li
g
h
t
G
B
M
0
.
9
5
7
4
0
.
9
5
8
4
0
.
9
6
0
.
9
5
0
.
9
7
0
.
9
3
0
.
9
7
0
.
9
4
TT
-
X
G
B
o
o
st
0
.
8
9
2
2
5
0
.
8
9
4
2
0
.
9
1
0
.
8
7
0
.
9
3
0
.
8
4
0
.
9
2
0
.
8
5
AE
-
X
G
B
o
o
st
0
.
9
7
7
3
0
.
9
7
7
3
0
.
9
8
0
.
9
7
0
.
9
8
0
.
9
7
0
.
9
8
0
.
9
7
T
ab
le
2
.
C
o
m
p
ar
ativ
e
p
er
f
o
r
m
an
ce
o
f
h
y
b
r
id
m
o
d
els b
ased
o
n
co
m
p
o
s
ite
ev
alu
atio
n
m
etr
ic
s
M
e
t
r
i
c
RF
Li
g
h
t
G
B
M
TT
-
X
G
B
o
o
st
AE
-
X
G
B
o
o
st
M
C
C
0
.
8
6
6
9
0
.
9
1
0
1
0
.
7
7
0
6
0
.
9
5
0
7
B
a
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I
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8
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Fig
u
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ates
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ates
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I
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2
2
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2
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
F
ea
tu
r
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tr
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n
s
fo
r
ma
tio
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emb
le
lea
r
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fo
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o
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er g
r
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ta
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ilit
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… (
S
ir
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h
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u
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o
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305
4.
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ted
a
t
e
m
a
il
:
k
a
v
it
h
a
.
a
k
k
i
1
5
1
4
@
g
m
a
il
.
c
o
m
.
Dr
.
Th
ik
k
a
R
a
m
a
K
a
n
a
k
a
Du
r
g
a
V
a
r
a
Pr
a
sa
d
is
w
o
rk
i
n
g
a
s
a
n
a
ss
istan
t
p
ro
fe
ss
o
r
in
th
e
De
p
a
rtme
n
t
o
f
E
n
g
i
n
e
e
rin
g
M
a
t
h
e
m
a
ti
c
s
a
n
d
H
u
m
a
n
it
ies
,
S
.
R.
K.R.
En
g
i
n
e
e
rin
g
C
o
ll
e
g
e
,
B
h
ima
v
a
ra
m
.
He
c
o
m
p
lete
d
h
is
P
h
.
D
.
in
2
0
2
3
fro
m
An
d
h
ra
Un
i
v
e
rsity
,
Vish
a
k
a
p
a
tn
a
m
.
He
h
a
s
1
8
y
e
a
rs
o
f
tea
c
h
i
n
g
e
x
p
e
rien
c
e
a
n
d
1
1
y
e
a
rs
o
f
re
se
a
rc
h
e
x
p
e
rien
c
e
.
He
p
u
b
li
sh
e
d
1
3
re
se
a
rc
h
p
a
p
e
rs
in
v
a
rio
u
s
i
n
tern
a
ti
o
n
a
l
jo
u
rn
a
ls.
He
h
a
s
p
u
b
li
s
h
e
d
2
p
a
ten
ts
a
n
d
o
n
e
b
o
o
k
c
h
a
p
ter.
He
q
u
a
li
fied
fo
r
APS
ET
-
2
0
2
3
.
His
re
se
a
rc
h
in
tere
st
i
n
c
lu
d
e
s
f
lu
i
d
d
y
n
a
m
ics
a
n
d
m
a
c
h
in
e
lea
rn
i
n
g
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
tr
k
d
v
p
ra
sa
d
@s
rk
re
c
.
a
c
.
in
.
Dr
.
Chu
k
k
a
R
a
ja
se
k
h
a
r
re
c
e
iv
e
d
h
is
B.
Tec
h
.
d
e
g
re
e
in
e
lec
tro
n
ics
a
n
d
c
o
m
m
u
n
ica
ti
o
n
e
n
g
i
n
e
e
rin
g
fro
m
JN
TU
Un
iv
e
rsity
,
A
.
P
.
,
In
d
ia,
in
2
0
0
6
,
a
n
d
th
e
M
.
Tec
h
.
d
e
g
re
e
in
ra
d
a
r
a
n
d
m
icro
wa
v
e
e
n
g
i
n
e
e
rin
g
fr
o
m
An
d
h
ra
Un
i
v
e
rsity
,
A.P
.
,
In
d
ia,
i
n
2
0
0
8
.
He
wa
s
a
wa
rd
e
d
a
P
h
.
D.
d
e
g
re
e
i
n
g
l
o
b
a
l
n
a
v
ig
a
ti
o
n
sa
telli
te
sy
ste
m
fro
m
t
h
e
De
p
a
rtme
n
t
o
f
El
e
c
tro
n
ics
a
n
d
Co
m
m
u
n
ica
ti
o
n
En
g
i
n
e
e
rin
g
,
JN
TUK,
Ka
k
i
n
a
d
a
,
A.P
.
,
I
n
d
ia
in
2
0
2
0
.
He
is
c
u
rre
n
tl
y
w
o
rk
i
n
g
a
s
a
n
a
ss
o
c
iate
p
ro
fe
ss
o
r
in
th
e
De
p
a
rt
m
e
n
t
o
f
El
e
c
tro
n
ics
a
n
d
Co
m
m
u
n
ica
ti
o
n
En
g
i
n
e
e
rin
g
,
A
d
it
y
a
Un
iv
e
rsity
,
S
u
ra
m
p
a
lem
,
An
d
h
ra
P
ra
d
e
sh
,
In
d
ia.
His
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
g
l
o
b
a
l
n
a
v
ig
a
ti
o
n
sa
telli
te
sy
ste
m
a
n
d
w
irele
ss
c
o
m
m
u
n
ica
ti
o
n
s.
He
p
u
b
li
sh
e
d
h
is
re
se
a
rc
h
p
a
p
e
rs
in
re
fe
re
e
d
in
tern
a
ti
o
n
a
l
j
o
u
r
n
a
ls
a
n
d
in
tern
a
ti
o
n
a
l
a
n
d
n
a
ti
o
n
a
l
c
o
n
fe
re
n
c
e
s.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
c
h
u
k
k
a
ra
jas
e
k
h
a
r@g
m
a
il
.
c
o
m
.
K
r
ish
n
a
Ra
o
Peda
d
a
is
c
u
r
re
n
tl
y
w
o
rk
i
n
g
a
s
a
n
a
ss
istan
t
p
ro
fe
ss
o
r
with
th
e
De
p
a
rtme
n
t
o
f
El
e
c
tro
n
ics
a
n
d
Co
m
m
u
n
ica
ti
o
n
En
g
i
n
e
e
rin
g
,
Ad
it
y
a
In
stit
u
te
o
f
Tec
h
n
o
lo
g
y
a
n
d
M
a
n
a
g
e
m
e
n
t,
Tek
k
a
li
.
He
is
p
u
rsu
i
n
g
P
h
.
D.
at
A
n
d
h
ra
Un
iv
e
r
sity
a
n
d
c
o
m
p
lete
d
M
.
Tec
h
.
in
VL
S
I
s
y
ste
m
d
e
sig
n
fro
m
JN
TUK,
Ka
k
in
a
d
a
.
He
h
a
s
p
u
b
li
sh
e
d
5
p
a
ten
ts
a
n
d
m
o
re
th
a
n
1
5
re
se
a
rc
h
p
a
p
e
rs
in
re
p
u
ted
in
tern
a
ti
o
n
a
l
a
n
d
n
a
ti
o
n
a
l
j
o
u
r
n
a
ls
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
p
k
r.
a
it
a
m
@g
m
a
il
.
c
o
m
.
Pro
f.
S
a
i
K
ira
n
O
r
u
g
a
n
ti
is
c
u
rre
n
tl
y
w
o
rk
i
n
g
a
s
a
n
a
ss
o
c
iate
p
ro
fe
ss
o
r
in
t
h
e
F
a
c
u
lt
y
o
f
E
n
g
i
n
e
e
rin
g
a
n
d
B
u
il
t
En
v
iro
n
m
e
n
t,
L
in
c
o
l
n
Un
iv
e
rsi
ty
Co
l
leg
e
,
Ku
a
la
L
u
m
p
u
r
,
M
a
lay
sia
.
He
is
a
lso
a
ffil
iate
d
with
th
e
Tec
h
n
o
l
o
g
y
In
n
o
v
a
ti
o
n
Hu
b
(TI
H),
In
d
ian
I
n
stit
u
te
o
f
Tec
h
n
o
l
o
g
y
P
a
tn
a
.
F
r
o
m
2
0
1
9
t
o
2
0
2
2
,
h
e
wa
s
a
ss
o
c
iate
d
with
t
h
e
S
c
h
o
o
l
o
f
El
e
c
tri
c
a
l
a
n
d
Au
to
m
a
ti
o
n
En
g
in
e
e
rin
g
,
Jia
n
g
x
i
Un
iv
e
rsity
o
f
S
c
ien
c
e
a
n
d
Tec
h
n
o
l
o
g
y
,
Ch
i
n
a
,
wh
e
re
h
e
c
o
n
tri
b
u
ted
to
th
e
e
sta
b
li
sh
m
e
n
t
o
f
a
n
a
d
v
a
n
c
e
d
wire
les
s
p
o
we
r
t
ra
n
sfe
r
re
se
a
rc
h
lab
o
ra
to
r
y
.
His
e
x
p
e
rti
se
li
e
s
in
wire
les
s
p
o
we
r
tran
sm
issio
n
th
r
o
u
g
h
ra
d
i
o
-
s
h
ield
e
d
z
o
n
e
s.
He
e
a
rn
e
d
h
is
P
h
.
D.
in
2
0
1
6
fro
m
th
e
Ulsa
n
N
a
ti
o
n
a
l
In
stit
u
te
o
f
S
c
ien
c
e
a
n
d
Tec
h
n
o
l
o
g
y
(UN
IS
T),
S
o
u
th
Ko
re
a
,
wh
e
re
h
e
d
e
v
e
lo
p
e
d
wire
les
s
c
o
m
m
u
n
ica
ti
o
n
sy
ste
m
s
fo
r
Hy
u
n
d
a
i
He
a
v
y
In
d
u
stries
a
n
d
S
a
m
su
n
g
He
a
v
y
In
d
u
stries
.
His
d
o
c
to
ra
l
wo
rk
led
t
o
t
h
e
c
re
a
ti
o
n
o
f
t
h
e
sp
i
n
-
o
ff
c
o
m
p
a
n
y
ZN
-
Oc
e
a
n
Tec
h
n
o
l
o
g
ies
.
He
h
a
s
p
re
v
io
u
sly
se
rv
e
d
a
s
a
fa
c
u
lt
y
m
e
m
b
e
r
a
t
IIT
Ti
r
u
p
a
ti
a
n
d
is
a
re
c
ip
ien
t
o
f
t
h
e
URSI
Yo
u
n
g
S
c
ien
ti
st
Aw
a
rd
(2
0
1
6
).
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
sa
ish
a
rm
a
@lin
c
o
ln
.
e
d
u
.
m
y
.
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