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[
1
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–
[
3
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.
T
h
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4
1
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R
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th
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[
4
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.
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s
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R
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m
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eq
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[
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T
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to
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I
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I
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2088
-
8
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Dete
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B
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11
d
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lan
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[
6
]
.
R
esear
ch
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s
h
av
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p
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h
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s
iv
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s
tu
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eth
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s
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h
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th
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.
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h
e
r
en
ewa
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-
b
ased
s
u
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ca
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tim
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ee
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g
g
r
id
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m
in
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ca
p
ab
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[
7
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.
T
h
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cr
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lan
d
in
g
in
s
ce
n
ar
io
s
with
m
i
n
im
u
m
p
o
wer
m
is
m
atch
with
i
n
m
icr
o
g
r
id
ca
lled
as
n
o
n
-
d
et
ec
tio
n
zo
n
e
(
NDZ
)
.
I
n
ac
tiv
e
m
eth
o
d
s
an
in
ten
ti
o
n
al
d
is
tu
r
b
an
ce
will
b
e
in
jecte
d
in
co
n
tr
o
ller
o
f
DG
s
u
ch
a
way
th
at
th
ese
d
is
tu
r
b
an
ce
s
do
not
af
f
ec
t
th
e
PC
C
p
ar
am
eter
u
n
d
er
an
y
o
f
th
e
non
-
is
lan
d
in
g
ev
en
ts
an
d
im
p
o
r
tan
tly
th
e
y
in
cr
ea
s
e
th
e
d
ev
iatio
n
o
n
l
y
d
u
r
in
g
is
lan
d
in
g
,
b
ased
o
n
wh
ic
h
th
e
is
lan
d
in
g
d
etec
tio
n
r
esu
l
ts
.
T
h
e
in
jectio
n
o
f
d
is
tu
r
b
an
ce
s
ca
u
s
es
p
o
wer
q
u
ality
d
eg
r
ad
atio
n
.
Hy
b
r
id
m
et
h
o
d
is
a
co
m
b
in
atio
n
o
f
b
o
t
h
p
ass
iv
e
an
d
ac
tiv
e
m
eth
o
d
s
,
th
e
th
r
esh
o
ld
b
ased
p
ar
am
eter
is
co
n
tin
u
o
u
s
ly
o
b
s
er
v
ed
if
it
ex
ce
ed
s
a
m
in
im
u
m
th
r
esh
o
ld
b
u
t
d
o
n
o
t
r
ea
ch
to
t
h
e
m
ax
im
u
m
o
n
ly
d
u
r
i
n
g
s
u
c
h
s
u
s
p
icio
u
s
o
cc
asio
n
s
o
f
is
lan
d
in
g
d
is
tu
r
b
an
ce
s
ig
n
al
is
in
tr
o
d
u
ce
d
at
PC
C
an
d
its
im
p
ac
t
is
o
b
s
er
v
ed
f
o
r
d
etec
tio
n
,
wh
ich
r
ed
u
ce
s
th
e
p
o
s
s
ib
ilit
ies
o
f
p
o
wer
q
u
ality
d
eg
r
ad
atio
n
[
8
]
.
Pas
s
iv
e
m
eth
o
d
s
,
b
ased
o
n
v
o
ltag
e
in
f
o
r
m
atio
n
at
PC
C
ar
e
s
im
p
le
an
d
f
aster
b
u
t
r
esu
lts
in
to
lar
g
er
NDZ
.
Sig
n
al
d
ec
o
m
p
o
s
itio
n
tech
n
iq
u
es,
co
m
b
in
ed
with
in
t
ellig
en
t
class
if
ier
s
,
o
f
f
er
a
s
o
lu
tio
n
to
o
v
er
co
m
e
th
ese
lim
itatio
n
s
.
T
h
ese
ap
p
r
o
ac
h
es
in
v
o
lv
e
e
x
tr
ac
tin
g
s
u
ita
b
le
f
ea
tu
r
es
f
r
o
m
th
e
s
ig
n
al
to
class
if
y
th
e
ev
en
t.
Patter
n
r
ec
o
g
n
itio
n
tec
h
n
iq
u
e
s
(
PR
T
s
)
l
ik
e
d
ec
is
io
n
tr
ee
(
DT
)
,
r
an
d
o
m
f
o
r
est
(
R
F),
SVM
h
elp
class
if
y
is
lan
d
in
g
an
d
n
o
n
-
is
lan
d
in
g
ev
en
ts
ac
cu
r
ately
,
e
n
h
an
ci
n
g
th
e
r
eliab
ilit
y
an
d
ef
f
ec
tiv
e
n
ess
o
f
is
lan
d
in
g
d
etec
tio
n
m
eth
o
d
s
.
2.
L
I
T
E
R
AT
U
RE
R
E
VI
E
W
Ma
n
y
h
a
v
e
tr
ied
d
if
f
er
e
n
t
m
eth
o
d
s
f
o
r
is
lan
d
in
g
d
etec
tio
n
o
f
m
icr
o
g
r
id
.
T
h
e
s
tu
d
ies
h
av
e
b
ee
n
f
o
cu
s
ed
o
n
p
ass
iv
e,
ac
tiv
e
an
d
h
y
b
r
id
m
eth
o
d
s
o
f
d
ete
ctio
n
,
h
o
wev
er
s
ig
n
al
p
r
o
ce
s
s
in
g
an
d
ar
tific
ial
in
tellig
en
ce
tech
n
iq
u
es
ar
e
i
n
v
esti
g
ated
r
ec
en
tly
.
T
h
e
r
a
te
o
f
ch
an
g
e
o
f
p
o
wer
f
ac
to
r
an
g
le
h
as
b
ee
n
co
n
s
id
er
ed
as
th
r
esh
o
ld
p
ar
a
m
eter
to
d
is
tin
g
u
is
h
th
e
is
lan
d
in
g
with
n
o
n
-
is
lan
d
in
g
e
v
en
ts
.
I
m
p
o
r
tan
tly
with
ch
an
g
in
g
lo
a
d
c
o
n
d
itio
n
th
e
th
r
esh
o
ld
p
ar
am
eter
h
as b
ee
n
m
ad
e
ad
a
p
tiv
e
wh
ic
h
r
esu
lts
in
i
m
p
r
o
v
e
d
ac
c
u
r
ac
y
.
I
t
h
as
b
ee
n
o
b
s
er
v
ed
th
at
ND
Z
is
r
ed
u
ce
d
c
o
m
p
ar
e
to
m
et
h
o
d
s
b
ased
o
n
d
f
/d
q
[
1
]
.
Stu
d
y
[
2
]
i
n
tr
o
d
u
ce
s
a
tech
n
iq
u
e
b
ased
o
n
th
e
r
ate
o
f
ch
an
g
e
o
f
p
o
wer
(
R
OC
OP)
u
s
in
g
ter
m
in
al
v
o
ltag
e
(
T
V)
o
f
th
e
p
h
o
to
v
o
ltaic
in
v
er
ter
a
n
d
d
etec
tio
n
ac
c
u
r
a
cy
h
as
b
ee
n
f
o
u
n
d
b
etter
th
a
n
f
ew
o
f
th
e
o
th
e
r
p
ass
iv
e
m
eth
o
d
s
,
b
u
t
f
ails
to
d
etec
t
is
lan
d
in
g
in
p
o
wer
m
atch
in
g
co
n
d
itio
n
.
Dete
ctio
n
u
s
in
g
r
ate
o
f
ch
an
g
e
o
f
p
o
w
er
an
g
le
d
ev
iatio
n
(
R
OC
O
PAD
)
h
as
b
ee
n
ev
al
u
ated
o
n
MA
T
L
AB
to
d
em
o
n
s
tr
ate
its
ef
f
ec
tiv
en
ess
in
ter
m
s
o
f
d
etec
tio
n
ac
cu
r
ac
y
a
n
d
d
etec
tio
n
tim
e
f
o
r
DG’
s
[
3
]
.
Ph
ase
an
g
le
o
f
p
o
s
itiv
e
s
eq
u
en
ce
v
o
lta
g
e
at
PC
C
h
as
b
ee
n
f
o
u
n
d
t
o
d
o
m
in
ate
is
lan
d
d
etec
tio
n
co
m
p
ar
e
to
o
th
e
r
co
n
v
en
tio
n
ally
u
s
ed
p
ar
am
eter
s
lik
e
f
r
e
q
u
e
n
cy
,
v
o
ltag
e,
ac
tiv
e
p
o
wer
,
r
ea
ctiv
e
p
o
wer
,
p
o
we
r
f
ac
to
r
an
d
to
tal
h
ar
m
o
n
ic
d
is
to
r
tio
n
(
T
HD)
[
4
]
.
T
h
ese
p
ass
iv
e
m
eth
o
d
s
ar
e
s
im
p
le
h
o
wev
er
r
esu
lts
in
lar
g
er
NDZ
.
T
h
e
p
er
tu
r
b
atio
n
in
th
e
in
v
er
t
er
’
s
o
u
tp
u
t
c
u
r
r
e
n
t
ca
u
s
es
v
o
lt
ag
e
v
ar
iatio
n
s
,
wh
ic
h
h
as
b
ee
n
o
b
s
er
v
e
d
as
an
im
p
ed
an
ce
f
o
r
m
u
lated
a
s
d
v
/d
i.
I
s
lan
d
in
g
is
d
etec
ted
wh
en
im
p
ed
an
ce
s
u
r
p
ass
es
th
r
esh
o
ld
im
p
ed
an
ce
v
alu
e.
T
h
e
m
eth
o
d
r
esu
lts
i
n
s
m
all
NDZ
with
0
.
7
7
-
0
.
9
5
s
ec
o
n
d
s
d
etec
tio
n
tim
e
in
s
in
g
le
-
DG
s
y
s
tem
s
.
Ho
wev
er
,
t
h
e
d
etec
tio
n
ac
c
u
r
ac
y
d
r
o
p
s
in
m
u
lti
-
in
v
e
r
ter
s
y
s
tem
s
[
5
]
.
T
h
e
San
d
ia
v
o
l
tag
e
s
h
if
t
m
et
h
o
d
in
tr
o
d
u
ce
s
a
p
o
s
itiv
e
f
ee
d
b
ac
k
m
ec
h
an
is
m
to
p
e
r
tu
r
b
t
h
e
v
o
ltag
e
am
p
litu
d
e
at
th
e
PC
C
b
y
in
jectin
g
r
ea
ctiv
e
p
o
wer
.
Un
d
er
g
r
i
d
c
o
n
n
ec
ted
ev
en
ts
m
i
n
im
al
im
p
ac
t
h
as
b
ee
n
o
b
s
er
v
ed
o
n
t
h
e
PC
C
v
o
ltag
e,
b
u
t
u
n
d
er
is
lan
d
in
g
co
n
d
itio
n
s
it
is
s
ig
n
if
ican
t
f
o
r
d
etec
tio
n
[
6
]
.
Mo
s
t
o
f
th
e
ac
tiv
e
m
et
h
o
d
s
r
esu
lt
s
in
r
ed
u
ce
d
NDZ
co
m
p
ar
e
to
p
ass
iv
e
m
eth
o
d
,
b
u
t d
u
e
to
in
jectio
n
o
f
d
is
tu
r
b
a
n
ce
s
ig
n
al
ca
u
s
es p
o
wer
q
u
ality
is
s
u
es.
H
y
b
r
i
d
i
s
l
a
n
d
i
n
g
d
e
t
e
ct
i
o
n
m
e
t
h
o
d
f
o
r
g
r
i
d
-
c
o
n
n
e
c
t
e
d
p
h
o
t
o
v
o
l
t
a
i
c
s
y
s
t
e
m
s
h
as
b
e
e
n
d
is
c
u
s
s
e
d
in
r
e
f
e
r
e
n
c
e
[
7
]
.
I
n
t
h
e
f
i
r
s
t
s
t
e
p
i
t
d
e
te
c
ts
a
p
o
t
e
n
ti
a
l
i
s
l
a
n
d
i
n
g
e
v
e
n
t
w
h
e
n
t
h
e
a
b
s
o
l
u
te
d
ev
i
a
t
i
o
n
o
f
t
h
e
PC
C
v
o
l
t
a
g
e
e
x
c
e
e
d
s
a
t
h
r
e
s
h
o
l
d
a
n
d
i
n
s
e
c
o
n
d
s
t
e
p
a
f
t
e
r
a
d
e
f
i
n
ed
d
e
l
a
y
a
t
r
a
n
s
i
e
n
t
d
is
t
u
r
b
a
n
c
e
i
s
i
n
j
e
ct
e
d
i
n
t
o
t
h
e
i
n
v
e
r
t
e
r
’
s
d
-
a
x
is
r
e
f
e
r
e
n
c
e
c
u
r
r
e
n
t
w
h
i
c
h
r
e
d
u
c
e
s
t
h
e
a
c
t
i
v
e
p
o
w
e
r
o
u
t
p
u
t
c
a
u
s
i
n
g
t
h
e
PC
C
v
o
l
t
a
g
e
t
o
d
r
o
p
o
n
l
y
d
u
r
i
n
g
i
s
l
a
n
d
i
n
g
.
S
t
u
d
y
[
8
]
p
r
o
p
o
s
e
s
a
m
e
t
h
o
d
f
o
r
i
n
v
e
r
t
e
r
-
b
a
s
e
d
D
Gs
.
B
i
d
i
r
e
c
t
i
o
n
al
r
e
a
c
t
i
v
e
p
o
w
e
r
v
a
r
i
a
t
i
o
n
i
s
t
r
i
g
g
e
r
e
d
o
n
l
y
w
h
e
n
v
o
l
t
a
g
e
u
n
b
a
l
a
n
c
e
(
V
U
)
/
T
H
D
s
u
s
p
e
cts
is
l
a
n
d
i
n
g
,
t
h
is
m
et
h
o
d
h
a
s
n
e
g
l
i
g
i
b
l
e
e
f
f
e
ct
s
o
n
p
o
w
e
r
f
a
c
t
o
r
.
A
h
y
b
r
i
d
t
e
c
h
n
iq
u
e
w
i
t
h
f
u
z
z
y
s
y
s
t
e
m
h
as
b
e
en
p
r
o
p
o
s
e
d
a
i
m
i
n
g
z
e
r
o
ND
Z
[
9
]
.
R
e
a
ct
i
v
e
p
o
we
r
i
n
j
e
c
t
i
o
n
as
a
d
is
t
u
r
b
a
n
c
e
w
i
ll
b
e
d
o
n
e
f
o
r
i
s
l
a
n
d
d
e
t
e
ct
i
o
n
,
t
h
e
T
H
D
d
u
e
t
o
i
n
j
e
ct
i
o
n
r
em
a
i
n
s
b
e
l
o
w
I
E
E
E
s
t
a
n
d
a
r
d
s
u
n
d
e
r
n
o
r
m
a
l
c
o
n
d
iti
o
n
.
I
n
h
y
b
r
i
d
m
e
t
h
o
d
s
t
h
e
i
n
tr
o
d
u
c
t
i
o
n
o
f
p
e
r
t
u
r
b
a
t
i
o
n
o
n
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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.
1
6
,
No
.
1
,
Feb
r
u
ar
y
20
2
6
:
10
-
24
12
Ar
tific
ial
n
eu
r
o
lo
g
ical
n
etwo
r
k
(
ANN)
m
eth
o
d
o
f
DT
c
h
ar
ac
ter
is
tics
h
as
b
ee
n
u
s
ed
f
o
r
is
lan
d
in
g
d
etec
tio
n
,
an
ac
cu
r
ac
y
o
f
9
9
.
1
%
h
as
b
ee
n
o
b
s
er
v
ed
,
b
u
t
r
esu
lts
in
m
o
r
e
co
m
p
u
tatio
n
tim
e
[
1
0
]
.
I
n
t
h
e
p
ap
e
r
[
1
1
]
it
is
p
r
o
p
o
s
ed
a
m
eth
o
d
f
o
r
is
lan
d
d
etec
tio
n
b
ased
o
n
g
en
etic
p
r
o
g
r
am
in
g
n
am
ed
as
ad
v
an
ce
d
is
lan
d
in
g
d
etec
tio
n
m
u
lti
-
g
en
e
g
e
n
etic
p
r
o
g
r
am
m
in
g
,
it
s
h
o
ws
t
h
e
p
er
f
o
r
m
a
n
ce
b
etter
th
a
n
A
NN
b
ased
m
et
h
o
d
s
,
h
o
wev
er
t
h
e
d
ata
s
et
u
s
ed
is
n
o
t
u
n
if
o
r
m
an
d
d
o
m
in
an
ce
o
f
n
o
n
-
is
lan
d
in
g
d
ata
is
o
b
s
e
r
v
ed
.
T
h
e
r
ef
er
en
ce
[
1
2
]
p
r
o
p
o
s
es
a
m
et
h
o
d
b
ased
o
n
d
ee
p
co
n
v
o
lu
tio
n
al
n
e
u
r
al
n
etwo
r
k
s
w
h
er
e
in
th
e
s
ig
n
al
s
ar
e
co
n
v
er
ted
to
2
D
im
ag
es
u
s
in
g
co
n
s
tan
t
Q
t
r
an
s
f
o
r
m
f
o
llo
wed
b
y
h
ier
a
r
c
h
ical
f
ea
tu
r
es
ex
tr
ac
tio
n
f
r
o
m
th
e
im
ag
es
f
o
r
PV
in
teg
r
ated
m
icr
o
g
r
id
s
.
T
h
e
in
tr
in
s
ic
m
o
d
e
f
u
n
ctio
n
s
(
I
MF’
s
)
o
f
th
e
v
o
ltag
e
o
b
ta
in
ed
b
y
em
p
i
r
ical
m
o
d
e
d
ec
o
m
p
o
s
itio
n
(
E
MD
)
h
av
e
b
ee
n
u
s
ed
f
o
r
d
etec
tio
n
an
d
th
e
m
eth
o
d
is
te
s
ted
f
o
r
m
icr
o
g
r
i
d
s
with
in
v
er
ter
an
d
d
ir
ec
t
f
ed
ty
p
es
o
f
d
is
tr
ib
u
ted
g
en
er
atio
n
s
[
1
3
]
.
Sli
d
in
g
win
d
o
w
d
is
cr
ete
Fo
u
r
ier
tr
an
s
f
o
r
m
an
d
E
MD
tech
n
iq
u
es
ar
e
u
s
ed
to
d
ec
o
m
p
o
s
e
cu
r
r
e
n
t
an
d
v
o
ltag
e
s
ig
n
al
in
to
I
MFs,
w
h
ich
h
av
e
b
ee
n
u
s
ed
f
o
r
ev
en
t id
en
tific
atio
n
.
Hig
h
class
if
icatio
n
ac
cu
r
ac
y
o
f
9
8
.
4
%,
d
etec
tio
n
tim
e
o
f
6
6
.
9
4
m
s
an
d
r
ed
u
ce
d
NDZ
h
as
b
ee
n
cl
aim
ed
in
th
e
p
ap
e
r
[
1
4
]
.
T
h
e
v
o
ltag
e
s
ig
n
al
at
P
C
C
h
as
b
ee
n
d
ec
o
m
p
o
s
ed
b
y
v
ar
iatio
n
al
m
o
d
e
d
ec
o
m
p
o
s
iti
o
n
(
VM
D)
to
o
b
tain
th
e
I
MF’
s
.
I
t
h
as
b
ee
n
s
h
o
wn
th
at
th
e
v
ar
iatio
n
in
en
er
g
y
o
f
I
MF
2
is
v
er
y
lo
w
f
o
r
n
o
n
-
is
lan
d
in
g
co
m
p
ar
e
to
is
lan
d
in
g
ev
en
ts
,
an
d
th
er
ef
o
r
e
u
s
ed
as a
th
r
esh
o
ld
p
ar
am
eter
.
T
h
e
NDZ
h
as r
esu
lted
in
les
s
th
an
1
%,
b
u
t o
n
ly
ac
tiv
e
p
o
wer
m
atch
in
g
c
o
n
d
it
io
n
s
h
av
e
b
ee
n
co
n
s
id
er
ed
[
1
5
]
.
An
is
lan
d
d
etec
tio
n
m
eth
o
d
f
o
r
p
h
o
to
v
o
ltaic
s
y
s
tem
s
wh
er
e
VM
D
p
r
o
ce
s
s
es
v
o
ltag
e
an
d
p
o
wer
s
ig
n
al
h
a
s
b
ee
n
p
r
o
p
o
s
ed
,
e
n
s
em
b
le
b
a
g
g
ed
-
tr
ee
s
m
eth
o
d
d
etec
ts
is
lan
d
in
g
ev
e
n
ts
ef
f
ec
tiv
ely
d
u
r
in
g
p
o
wer
m
is
m
atc
h
ev
e
n
ts
with
d
etec
tio
n
tim
e
o
f
4
.
8
m
illi
s
ec
o
n
d
s
an
d
r
esu
lts
in
a
NDZ
o
f
less
th
an
4
%
[
1
6
]
.
T
h
e
s
tu
d
y
ca
r
r
ied
o
u
t
in
[
1
7
]
p
r
o
p
o
s
es
an
is
lan
d
in
g
d
etec
t
io
n
ap
p
r
o
ac
h
b
ased
o
n
d
is
cr
e
te
Fo
u
r
ier
tr
an
s
f
o
r
m
an
d
DT
wh
ich
h
as
b
ee
n
test
ed
o
n
a
m
icr
o
g
r
id
eq
u
ip
p
ed
with
s
y
n
ch
r
o
n
o
u
s
g
en
e
r
ato
r
.
T
h
e
d
etec
tio
n
r
esu
lts
with
in
th
r
ee
cy
cles
o
f
th
e
s
ig
n
al.
I
s
lan
d
in
g
d
etec
tio
n
in
m
u
ltip
le
DG
m
icr
o
g
r
i
d
u
s
in
g
d
is
cr
ete
wav
elet
tr
an
s
f
o
r
m
f
o
r
ex
tr
ac
tin
g
u
n
b
alan
ce
d
v
o
ltag
e
ch
ar
ac
ter
is
tic
s
h
as
b
ee
n
d
is
cu
s
s
ed
.
R
F
ap
p
r
o
ac
h
is
u
s
ed
f
o
r
class
if
icatio
n
,
im
p
o
r
tan
tly
d
i
v
er
s
e
o
p
er
atin
g
c
o
n
d
itio
n
s
a
r
e
co
n
s
id
er
ed
f
o
r
p
e
r
f
o
r
m
an
ce
test
in
g
an
d
f
o
u
n
d
ef
f
ec
tiv
e
[
1
8
]
.
A
m
eth
o
d
b
ased
o
n
R
F
ap
p
r
o
ac
h
with
ef
f
ec
t
iv
e
u
tili
za
tio
n
o
f
h
is
to
g
r
am
o
f
o
r
ien
ted
g
r
a
d
ien
ts
(
HOG
)
f
ea
tu
r
es
f
o
r
p
atter
n
r
ec
o
g
n
itio
n
is
p
r
o
p
o
s
ed
in
[
1
9
]
a
n
d
an
ac
c
u
r
ac
y
o
f
9
8
.
7
5
%
h
as
b
ee
n
claim
ed
with
192
m
s
o
f
d
etec
tio
n
tim
e.
F
ast
d
is
cr
ete
S
-
tr
an
s
f
o
r
m
(
FDST)
an
d
b
id
ir
ec
tio
n
al
ex
tr
em
e
lear
n
in
g
m
ac
h
i
n
e
(
B
E
L
M)
h
as
b
ee
n
u
s
ed
o
n
n
e
g
ativ
e
s
eq
u
en
ce
v
o
ltag
e
an
d
cu
r
r
en
t
s
ig
n
als
at
th
e
DG
en
d
f
o
r
d
etec
tio
n
.
T
h
e
f
ea
tu
r
es su
ch
as e
n
er
g
y
,
s
tan
d
ar
d
d
ev
iatio
n
o
f
th
e
s
ig
n
al
h
as
b
ee
n
s
elec
ted
f
o
r
class
if
icatio
n
.
T
h
e
ac
cu
r
ac
y
h
as
b
ee
n
f
o
u
n
d
to
b
e
9
1
.
5
%
with
n
o
is
e
o
f
2
0
d
B
,
h
o
wev
er
tr
a
in
in
g
d
ata
s
et
h
as
b
ee
n
f
o
u
n
d
b
iased
[
2
0
]
.
T
h
e
f
ea
tu
r
es
o
f
v
o
ltag
e
,
cu
r
r
e
n
t
an
d
f
r
eq
u
e
n
cy
at
PC
C
h
av
e
b
ee
n
ex
tr
ac
ted
u
s
in
g
wav
elet
tr
a
n
s
f
o
r
m
f
o
r
an
aly
s
is
an
d
h
a
v
e
b
ee
n
u
s
ed
with
m
ac
h
in
e
lear
n
in
g
(
ML
)
,
an
ac
cu
r
ac
y
o
f
9
7
.
9
%
o
n
tr
ain
ed
d
ata
h
as
b
ee
n
o
b
s
er
v
e
d
with
tr
ain
in
g
tim
e
o
f
1
6
.
9
s
ec
o
n
d
s
[
2
1
]
.
T
h
e
s
tu
d
y
f
o
cu
s
es
o
n
d
etec
tin
g
u
n
in
ten
tio
n
al
is
lan
d
in
g
u
s
in
g
m
ac
h
in
e
lear
n
in
g
f
o
r
a
g
r
id
-
co
n
n
ec
ted
PV
s
y
s
tem
.
T
h
e
u
s
e
o
f
p
h
aso
r
m
ea
s
u
r
e
m
en
t u
n
its
(
P
MU
)
f
o
r
r
ec
o
r
d
in
g
b
ig
d
ata
h
as
b
ee
n
u
s
ef
u
l
f
o
r
is
lan
d
in
g
d
etec
tio
n
[
2
2
]
.
T
h
e
d
is
cu
s
s
io
n
o
f
p
r
e
-
p
r
o
ce
s
s
in
g
s
tep
s
in
ar
tific
ial
n
eu
r
al
n
etwo
r
k
s
f
o
r
class
if
icatio
n
r
elate
d
to
is
lan
d
in
g
s
u
ch
a
s
lo
ad
in
g
d
ata
f
r
o
m
a
C
SV
f
ile,
h
an
d
lin
g
m
is
s
in
g
v
alu
es,
f
ea
tu
r
e
s
ca
lin
g
,
an
d
en
co
d
in
g
ca
teg
o
r
ical
f
ea
tu
r
es,
d
escr
ip
tio
n
o
f
th
e
m
o
d
elin
g
p
r
o
ce
s
s
u
s
in
g
th
e
R
F,
in
clu
d
in
g
d
ataset
s
p
litt
in
g
,
an
d
DT
co
n
s
tr
u
ctio
n
.
h
as
b
ee
n
d
o
n
e
[
2
3
]
.
R
F
ap
p
r
o
ac
h
f
o
r
is
lan
d
in
g
d
etec
tio
n
in
DC
m
icr
o
g
r
id
h
as
b
ee
n
p
r
o
p
o
s
ed
in
[
2
4
]
.
E
x
tr
ac
tin
g
in
d
e
x
e
s
,
lik
e
cu
r
r
en
t,
v
o
ltag
e,
o
u
tp
u
t
p
o
wer
,
an
d
th
eir
f
ir
s
t
-
o
r
d
er
b
ac
k
war
d
d
if
f
er
e
n
ce
to
ef
f
ec
tiv
ely
d
is
tin
g
u
is
h
is
lan
d
in
g
f
r
o
m
n
o
n
-
is
lan
d
in
g
co
n
d
itio
n
s
b
y
p
r
o
ce
s
s
in
g
lar
g
e
d
atasets
.
Stan
d
ar
d
ized
test
p
r
o
ce
d
u
r
es
an
d
g
u
i
d
elin
es
f
o
r
ev
al
u
atin
g
is
lan
d
d
etec
tio
n
m
eth
o
d
s
wo
u
ld
en
h
an
ce
th
e
co
m
p
ar
a
b
ilit
y
an
d
r
eliab
il
ity
o
f
f
u
tu
r
e
s
tu
d
ies
in
th
is
ar
ea
[
2
5
]
.
T
h
e
s
tan
d
ar
d
test
p
r
o
ce
d
u
r
e
f
o
r
is
lan
d
d
etec
tio
n
is
d
if
f
er
en
t
f
o
r
v
a
r
io
u
s
co
u
n
tr
ies,
h
o
wev
e
r
in
m
o
s
t
o
f
th
e
ap
p
r
o
ac
h
es
to
h
av
e
g
en
er
o
s
ity
R
-
L
-
C
p
ar
allel
co
m
b
in
atio
n
h
as
b
ee
n
co
n
s
id
er
ed
as
lo
ad
s
in
ce
is
lan
d
d
etec
tio
n
is
ch
allen
g
in
g
u
n
d
er
s
u
ch
co
n
d
itio
n
s
.
T
h
e
p
o
ten
tial
in
teg
r
atio
n
o
f
M
L
,
ar
tific
ial
in
tellig
en
ce
(
AI
)
tech
n
o
lo
g
ies
h
as
also
b
ee
n
u
n
d
er
lin
ed
[
2
6
]
.
Stu
d
y
[
2
7
]
s
u
m
m
ar
izes isl
an
d
in
g
d
et
ec
tio
n
s
tan
d
ar
d
s
in
v
ar
io
u
s
co
u
n
tr
ies.
R
esear
ch
er
s
h
av
e
in
v
esti
g
ated
p
ass
iv
e,
ac
tiv
e
an
d
h
y
b
r
i
d
m
eth
o
d
s
o
f
d
etec
tio
n
a
n
d
f
in
d
s
th
e
s
co
p
e
f
o
r
im
p
r
o
v
e
m
en
t.
T
h
e
liter
atu
r
e
r
ev
iew
ca
r
r
ied
o
u
t
u
n
d
er
lin
es
th
e
p
o
s
s
ib
ilit
ies
o
f
en
h
an
ce
m
en
t
u
s
in
g
a
d
v
an
ce
s
ig
n
al
p
r
o
ce
s
s
in
g
tec
h
n
iq
u
es
an
d
v
ar
io
u
s
AI
m
et
h
o
d
s
.
T
h
e
p
ap
e
r
is
o
r
g
an
ized
in
th
e
f
o
llo
win
g
m
an
n
er
Sectio
n
3
b
r
ief
s
m
o
tiv
atio
n
a
n
d
p
r
o
b
lem
d
ef
in
itio
n
,
s
ec
tio
n
4
d
etails
th
e
p
r
o
p
o
s
ed
m
eth
o
d
with
s
u
b
s
ec
tio
n
s
co
v
er
in
g
th
e
d
ata
g
e
n
er
atio
n
,
s
ig
n
al
d
ec
o
m
p
o
s
itio
n
,
f
ea
t
u
r
e
ex
tr
ac
tio
n
,
a
n
d
e
v
en
t
d
etec
tio
n
b
y
SVM.
Sectio
n
5
d
ea
ls
with
f
o
r
r
esu
lts
in
ter
m
s
o
f
ac
cu
r
ac
y
,
p
r
e
d
ictio
n
tim
e
an
d
NDZ
.
Sectio
n
6
co
n
clu
d
es th
e
p
ap
er
.
3.
M
O
T
I
VAT
I
O
N
AND
P
RO
B
L
E
M
DE
F
I
NA
T
I
O
N
Mo
s
t o
f
th
e
g
r
id
co
n
n
ec
ted
m
i
cr
o
g
r
id
/DG
s
y
s
tem
s
ar
e
u
n
d
er
u
tili
ze
d
d
u
e
to
th
e
n
ee
d
o
f
im
p
o
s
in
g
P
-
Q
co
n
tr
o
l
in
g
r
i
d
co
n
n
ec
ted
m
o
d
e
an
d
f
-
V
c
o
n
tr
o
l
in
is
lan
d
e
d
m
o
d
e
.
T
h
e
p
r
im
a
r
y
r
e
q
u
ir
e
m
en
t
f
o
r
ass
ig
n
in
g
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
Dete
ctio
n
o
f isl
a
n
d
in
g
u
s
in
g
e
mp
ir
ica
l m
o
d
e
d
ec
o
mp
o
s
itio
n
a
n
d
…
(
B
a
lw
a
n
t P
a
til
)
13
th
ese
co
n
tr
o
ls
is
ac
cu
r
ate
d
etec
tio
n
o
f
is
lan
d
in
g
i.e
.
th
e
r
es
u
lted
ev
en
t
is
a
non
-
is
lan
d
in
g
ev
en
t
lik
e
in
ter
n
al
f
au
lts
o
r
is
lan
d
in
g
i.e
.
th
e
s
ep
ar
atio
n
o
f
t
h
e
m
icr
o
g
r
id
f
r
o
m
th
e
m
ain
g
r
i
d
.
T
h
e
o
p
er
atin
g
co
n
d
itio
n
s
o
f
m
icr
o
g
r
id
f
o
r
wh
ich
th
e
e
x
is
tin
g
m
eth
o
d
s
f
ail
to
d
etec
t
th
e
i
s
lan
d
in
g
ca
lled
as
NDZ
o
r
f
al
s
e
id
en
tific
atio
n
o
f
th
e
ev
en
t
h
ap
p
en
s
.
I
f
is
lan
d
in
g
ev
en
t
is
wr
o
n
g
l
y
id
en
tifie
d
as
n
o
n
-
is
lan
d
in
g
a
n
d
if
P
-
Q
co
n
tr
o
l
is
ass
ig
n
ed
th
en
is
s
u
es
l
ik
e
v
o
ltag
e
d
r
if
t,
u
n
s
tab
le
f
r
eq
u
en
c
y
,
p
o
wer
im
b
alan
ce
,
lo
ad
s
h
ar
in
g
is
s
u
es
a
n
d
s
y
s
tem
co
llap
s
e
as
well
m
ay
r
esu
lt,
o
n
th
e
o
t
h
er
h
an
d
if
f
-
V
co
n
t
r
o
l
is
ap
p
li
ed
d
u
r
in
g
g
r
id
c
o
n
n
ec
te
d
m
o
d
e
it
m
ay
r
esu
lt
in
to
d
estab
ilizatio
n
o
f
PC
C
,
in
ap
p
r
o
p
r
iate
P
-
Q
in
jectio
n
,
o
v
e
r
lo
a
d
in
g
,
u
n
d
e
r
lo
ad
i
n
g
o
r
ev
e
n
s
y
s
tem
f
ailu
r
e
d
u
e
to
f
r
eq
u
e
n
cy
c
o
n
f
lict.
Ultim
atel
y
to
e
n
s
u
r
e
s
af
e,
s
tab
le
an
d
ec
o
n
o
m
ic
o
p
er
atio
n
o
f
g
r
id
c
o
n
n
ec
ted
m
icr
o
g
r
id
p
r
ec
is
e
d
etec
tio
n
o
f
th
e
is
lan
d
in
g
an
d
n
o
n
-
is
lan
d
in
g
ev
en
ts
an
d
ass
o
ciate
d
co
n
tr
o
ls
ar
e
n
e
ce
s
s
ar
y
.
T
h
e
s
tu
d
y
u
n
d
er
tak
e
n
ad
d
r
ess
es
ac
cu
r
ate
d
etec
tio
n
o
f
th
e
is
lan
d
in
g
an
d
n
o
n
-
is
lan
d
in
g
e
v
en
ts
wh
ich
is
th
e
p
r
im
ar
y
a
n
d
cr
u
cial
r
eq
u
ir
e
m
en
t o
f
th
e
m
ic
r
o
g
r
id
co
n
tr
o
l o
p
e
r
atio
n
.
4.
P
RO
P
O
SE
D
M
E
T
H
O
D
Simp
licity
o
f
p
ass
iv
e
m
eth
o
d
s
,
th
e
ad
v
an
ce
d
s
ig
n
al
p
r
o
ce
s
s
in
g
to
o
ls
,
AI
-
ML
tec
h
n
i
q
u
es,
I
C
tech
n
o
lo
g
y
with
b
etter
co
m
p
u
tatio
n
p
o
s
s
ib
ilit
ies
en
co
u
r
ag
es
to
ca
r
r
y
o
u
t
th
e
r
esear
ch
s
tu
d
ies
f
o
r
th
e
en
h
an
ce
m
e
n
t
o
f
p
ass
iv
e
m
eth
o
d
s
.
T
h
e
3
-
p
h
ase
v
o
ltag
e
s
ig
n
al
ex
tr
ac
ted
f
r
o
m
th
e
PC
C
ex
p
er
ien
ce
s
v
ar
iatio
n
s
d
u
r
in
g
is
lan
d
in
g
,
f
au
lts
,
an
d
l
o
ad
s
witch
in
g
.
Sig
n
al
d
ec
o
m
p
o
s
itio
n
f
u
r
th
e
r
d
etails
ev
en
th
e
m
in
u
te
v
ar
iatio
n
s
an
d
ML
b
ei
n
g
th
e
b
est to
o
l to
d
if
f
er
en
tiate
th
ese
v
a
r
iatio
n
s
,
it h
as b
ee
n
u
s
ed
t
o
class
if
y
th
e
ev
en
ts
.
T
h
e
h
ig
h
in
er
tia
o
f
f
e
r
ed
b
y
s
y
n
ch
r
o
n
o
u
s
g
en
er
at
o
r
o
f
th
e
m
i
cr
o
g
r
id
ca
u
s
es
m
in
im
al
v
ar
iatio
n
s
in
th
e
th
r
esh
o
ld
p
ar
a
m
eter
s
r
ef
er
r
e
d
f
o
r
is
lan
d
in
g
d
etec
tio
n
r
esu
ltin
g
in
to
NDZ
.
T
h
er
ef
o
r
e,
it
is
im
p
o
r
tan
t
to
co
n
s
id
er
a
m
icr
o
g
r
id
c
o
n
s
is
ts
o
f
s
y
n
ch
r
o
n
o
u
s
g
en
e
r
ato
r
al
o
n
g
with
PV
g
en
e
r
ato
r
f
o
r
th
e
s
tu
d
y
,
s
o
th
at
th
e
p
r
o
f
icien
c
y
o
f
th
e
d
etec
tio
n
m
eth
o
d
ca
n
b
e
u
n
d
er
lin
ed
.
T
h
e
s
y
s
tem
u
n
d
er
s
tu
d
y
c
o
n
s
is
ts
o
f
1
0
MV
A,
3
3
k
V
g
r
id
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s
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n
c
h
r
o
n
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e
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ato
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o
f
0
.
7
5
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MW,
PV
g
en
er
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o
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f
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an
d
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,
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r
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Fig
u
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ased
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et
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d
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im
p
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n
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n
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b
e
co
n
s
is
ten
t
f
o
r
p
r
ec
is
e
d
etec
tio
n
[
1
]
,
[
2
]
.
Fre
q
u
en
cy
v
ar
iatio
n
s
o
f
t
h
e
PC
C
v
o
ltag
e
ar
e
f
o
u
n
d
s
im
ilar
f
o
r
is
lan
d
in
g
an
d
n
o
n
-
is
lan
d
in
g
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.
1
6
,
No
.
1
,
Feb
r
u
ar
y
20
2
6
:
10
-
24
14
ev
en
ts
an
d
ar
e
n
o
t
alwa
y
s
s
u
f
f
icien
t
en
o
u
g
h
to
d
is
tin
g
u
is
h
t
h
em
.
Als
o
,
it
is
ex
p
ec
ted
t
h
at
it
r
em
ain
s
cr
o
s
s
in
g
th
e
th
r
esh
o
ld
at
least
f
o
r
4
0
m
s
f
o
r
d
etec
tio
n
.
Fig
u
r
e
2
s
h
o
ws
f
r
eq
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en
c
y
v
ar
iatio
n
s
d
u
r
in
g
is
lan
d
in
g
an
d
Fig
u
r
e
3
s
h
o
ws f
r
e
q
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en
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n
s
f
o
r
L
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f
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lt a
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ic
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Fig
u
r
e
2
.
C
h
an
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e
in
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o
f
PC
C
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u
r
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ter
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co
m
p
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n
en
ts
.
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asically
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a
n
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n
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s
tatio
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g
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ch
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o
o
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lik
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wav
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let
tr
an
s
f
o
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m
s
,
s
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Fo
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u
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es f
o
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class
if
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p
lin
g
f
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eq
u
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cy
:
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o
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p
tu
r
e
th
e
m
o
s
t
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s
s
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le
d
etails
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a
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o
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s
s
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n
al,
t
h
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p
lin
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r
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u
en
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m
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s
t
b
e
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g
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e
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g
h
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n
th
e
wo
r
k
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r
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t
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am
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s
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th
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al.
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im
e
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am
p
l
e
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s
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d
Sam
p
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r
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u
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cy
(
f
s
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tio
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(
1
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.
=
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4
.
2
.
Sig
na
l
deco
m
po
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it
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n
T
h
e
v
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ltag
e
s
ig
n
al
at
PC
C
d
u
r
in
g
is
lan
d
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g
a
n
d
f
au
lts
b
eh
a
v
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non
-
lin
ea
r
a
n
d
n
o
n
-
s
tatio
n
ar
y
.
T
h
e
d
ec
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m
p
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s
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o
f
s
u
ch
a
s
i
g
n
al
u
s
in
g
Fo
u
r
ie
r
tr
an
s
f
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m
(
FT)
ass
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es
th
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,
W
av
elet
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e
f
air
ly
g
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jo
b
b
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h
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f
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E
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e
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al
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to
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f
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d
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d
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f
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n
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allo
win
g
t
h
e
s
ep
ar
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o
f
h
ig
h
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f
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q
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en
c
y
f
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m
l
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w
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f
r
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en
d
s
co
n
tain
in
g
in
f
o
r
m
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n
s
u
itab
le
f
o
r
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en
t
id
en
tifi
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tio
n
.
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MD
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n
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n
co
v
er
h
id
d
en
p
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d
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d
tr
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eh
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ich
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t
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in
g
is
th
e
f
ea
tu
r
e
o
f
E
MD
wh
ich
p
r
o
v
id
es
a
tim
e
-
f
r
eq
u
en
cy
r
e
p
r
es
en
tatio
n
o
f
th
e
s
ig
n
al,
i.e
.
c
h
an
g
in
g
f
r
eq
u
e
n
cy
co
n
ten
t
o
f
n
o
n
-
s
tatio
n
ar
y
s
ig
n
als.
E
MD
h
elp
s
id
en
tify
ir
r
eg
u
lar
v
o
ltag
e
f
lu
ctu
atio
n
s
o
r
tr
a
n
s
ien
ts
in
elec
tr
ical
s
ig
n
als.
T
h
e
E
MD
f
lo
w
ch
ar
t i
s
s
h
o
wn
in
Fig
u
r
e
5
an
d
th
e
al
g
o
r
ith
m
h
as b
ee
n
d
escr
ib
ed
b
e
lo
w
f
u
r
th
er
.
I
MF
1
r
ep
r
esen
ts
th
e
h
ig
h
est
f
r
eq
u
en
c
y
co
n
ten
t
in
th
e
s
ig
n
al
wh
ich
in
d
icate
s
s
u
d
d
e
n
ch
an
g
es,
tr
an
s
ien
ts
an
d
s
o
m
etim
es
h
ig
h
f
r
e
q
u
en
c
y
n
o
is
e.
Hig
h
f
r
e
q
u
en
cy
co
m
p
o
n
en
ts
a
r
e
p
r
o
n
e
d
u
r
i
n
g
is
lan
d
i
n
g
,
wh
er
ea
s
I
MF
2
r
e
f
lects
r
elativ
e
ly
lo
wer
f
r
eq
u
en
cy
an
d
s
u
s
tain
ed
c
h
an
g
es
i
n
v
o
ltag
e
w
h
ich
m
ay
r
esu
lt
d
u
e
to
f
au
lts
at
f
ar
en
d
f
r
o
m
PC
C
.
T
h
er
ef
o
r
e,
th
e
in
f
o
r
m
atio
n
o
b
tai
n
ed
f
r
o
m
b
o
th
I
MF’
s
is
u
s
ef
u
l,
h
o
wev
er
I
MF
1
h
as
b
ee
n
u
s
ed
in
th
e
wo
r
k
ca
r
r
ie
d
o
u
t.
T
h
e
I
MF’
s
p
lo
t f
o
r
o
n
e
o
f
th
e
ev
en
ts
h
as b
ee
n
s
h
o
wn
in
Fig
u
r
e
6
.
Alg
o
r
ith
m
1
.
E
MD
alg
o
r
ith
m
Step
1
: T
h
e
s
am
p
led
tim
e
s
er
i
es d
ata
o
f
all
p
h
ases
is
tr
ea
ted
as si
g
n
al
(
)
.
Step
2
: D
eter
m
in
e
all
th
e
lo
ca
l
m
ax
im
a
an
d
m
in
im
a
o
f
(
)
.
Step
3
:
I
n
ter
p
o
late
m
ax
im
a
an
d
m
in
im
a
to
f
o
r
m
u
p
p
er
an
d
l
o
wer
en
v
elo
p
es
(
)
an
d
m
i
n
(
t
)
an
d
co
m
p
u
te
th
e
m
ea
n
,
(
)
=
(
(
)
+
m
i
n
(
t
)
)
/
2
.
Step
4
:
Su
b
tr
ac
t
(
)
f
r
o
m
t
h
e
o
r
i
g
in
al
s
ig
n
al:
ℎ
(
)
=
(
)
−
(
)
.
I
f
ℎ
(
)
s
atis
f
ies
th
e
co
n
d
itio
n
s
i.e
.
it
is
m
ea
n
v
alu
e
is
clo
s
e
to
ze
r
o
th
en
ℎ
(
)
is
co
n
s
id
er
ed
as
I
MF
1
.
E
ls
e,
r
ep
ea
t
s
tep
s
1
-
4
co
n
s
id
er
i
n
g
ℎ
(
)
as
x
(
t)
.
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.
1
6
,
No
.
1
,
Feb
r
u
ar
y
20
2
6
:
10
-
24
16
Step
5
: O
n
ce
an
is
id
en
tifie
d
,
s
u
b
tr
ac
t it
f
r
o
m
t
h
e
s
ig
n
al:
(
)
=
(
)
−
Step
6:
If
(
)
is
m
o
n
o
to
n
e
th
en
e
n
d
th
e
p
r
o
ce
s
s
,
else
tr
ea
t
(
)
as
(
)
a
n
d
p
r
o
ce
s
s
it
ag
ain
u
n
til
(
)
r
esu
lts
in
m
o
n
o
to
n
e.
Fig
u
r
e
5
.
E
MD
f
l
o
w
ch
ar
t
Nu
m
b
er
o
f
cy
cles in
I
MF
1
: 6
9
0
Fre
q
u
en
cy
o
f
I
MF
1
: 1
3
8
7
1
.
3
1
4
6
Hz
Nu
m
b
er
o
f
cy
cles in
I
MF
2
: 3
9
Fre
q
u
en
cy
o
f
I
MF
2
: 8
5
3
.
1
0
4
1
Hz
Ma
x
T
im
e
tak
en
to
ex
tr
ac
t
I
M
F
1
:
0
.
0
6
1
8
7
1
s
ec
o
n
d
s
(
v
ar
ies f
r
o
m
3
0
to
6
1
.
8
7
m
s
)
Fig
u
r
e
6
.
R
esu
ltin
g
I
MF’
s
u
s
in
g
E
MD
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
Dete
ctio
n
o
f isl
a
n
d
in
g
u
s
in
g
e
mp
ir
ica
l m
o
d
e
d
ec
o
mp
o
s
itio
n
a
n
d
…
(
B
a
lw
a
n
t P
a
til
)
17
4
.
3
.
F
ea
t
ure
s
elec
t
io
n
Ap
p
r
o
p
r
iate
s
tatis
tical
f
ea
tu
r
e
s
elec
tio
n
in
class
if
icatio
n
p
r
o
b
lem
is
im
p
o
r
tan
t.
I
n
th
e
w
o
r
k
c
ar
r
ied
o
u
t n
in
e
p
r
o
m
i
n
en
t f
ea
tu
r
es a
p
p
licab
le
f
o
r
tim
e
s
er
ies d
ata
h
a
v
e
b
ee
n
c
o
n
s
id
er
ed
an
d
d
is
cu
s
s
ed
b
elo
w.
−
Mean
(
M)
is
o
n
e
o
f
th
e
b
asic
f
ea
tu
r
es
wh
ich
is
co
m
p
u
ted
as
th
e
av
er
ag
e
v
alu
e
o
f
a
s
ig
n
al
(
)
f
o
r
m
u
lated
as
g
iv
en
in
(
3
)
.
I
t
r
ed
u
ce
s
d
ata
co
m
p
lex
ity
k
ee
p
in
g
im
p
o
r
tan
t
in
f
o
r
m
atio
n
o
f
th
e
s
ig
n
al
u
s
ef
u
l
f
o
r
class
if
icatio
n
.
=
1
∑
(
)
=
1
(
3
)
wh
er
e
is
th
e
n
u
m
b
er
o
f
d
ata
p
o
in
ts
in
th
e
d
ataset.
−
Stan
d
ar
d
d
e
v
iatio
n
(
)
r
ep
r
esen
ted
in
(
4
)
is
co
n
s
id
er
ed
as
s
ec
o
n
d
f
ea
t
u
r
e.
A
lo
w
v
alu
e
f
o
r
v
o
ltag
e
at
PC
C
in
d
icate
s
s
tab
le
g
r
id
o
p
er
atio
n
,
wh
er
ea
s
h
ig
h
er
v
alu
es
ar
e
in
d
icativ
e
o
f
ev
e
n
ts
lik
e
is
lan
d
in
g
o
r
f
au
lts
.
=
√
1
∑
(
(
)
−
)
=
1
2
(
4
)
−
Sk
ewn
ess
(
S
)
is
a
m
ea
s
u
r
e
to
q
u
an
tify
th
e
d
eg
r
ee
o
f
asy
m
m
etr
y
in
th
e
s
ig
n
al,
f
o
r
m
u
lated
as
g
iv
en
in
(
5
)
.
Po
s
itiv
e
S
in
d
icate
s
im
b
alan
ce
s
o
r
tr
an
s
ien
ts
wh
er
ea
s
n
eg
ativ
e
S
r
ef
lects v
ar
iatio
n
s
lik
e
v
o
lt
ag
e
s
ag
s
.
=
(
−
1
)
(
−
2
)
∑
(
(
(
)
−
)
)
3
=
1
(
5
)
−
Ku
r
to
s
is
(
K
)
r
ef
lects
th
e
o
u
tlier
s
,
s
u
ch
d
ata
m
ay
b
e
f
o
u
n
d
u
s
ef
u
l
f
o
r
d
etec
tin
g
s
witch
in
g
ev
en
ts
lik
e
is
lan
d
in
g
an
d
f
au
lts
,
an
d
it is
e
x
p
r
ess
ed
in
(
6
).
=
(
+
1
)
(
−
1
)
(
−
2
)
(
−
3
)
∑
(
=
1
(
(
)
−
/
)
4
−
3
(
−
1
)
2
/
(
−
2
)
(
−
3
)
)
(
6
)
−
Har
m
o
n
ic
d
is
to
r
tio
n
s
ar
e
m
ea
s
u
r
ed
b
y
t
o
tal
h
ar
m
o
n
ic
d
is
to
r
tio
n
(
T
HD)
g
iv
e
n
in
(
7
)
,
T
HD
g
ets
in
f
lu
en
ce
d
lar
g
ely
d
u
r
in
g
is
lan
d
in
g
an
d
f
a
u
lt e
v
en
ts
.
=
√
2
2
+
3
2
+
4
2
+
⋯
+
2
1
(
7
)
1
: A
m
p
litu
d
e
o
f
t
h
e
f
u
n
d
am
e
n
tal
f
r
eq
u
e
n
cy
,
2
,
3
,
…
,
:
Am
p
litu
d
es o
f
t
h
e
h
ig
h
e
r
o
r
d
er
h
a
r
m
o
n
ics.
Su
d
d
en
v
ar
iatio
n
s
in
s
ig
n
al
en
er
g
y
(
E
)
r
ef
lects
u
n
co
m
m
o
n
p
atter
n
s
in
v
o
ltag
e
s
ig
n
al
in
d
icate
s
h
ap
p
en
i
n
g
o
f
th
e
ev
e
n
ts
.
I
t is f
o
r
m
u
lated
as g
i
v
en
in
(
8
).
=
∑
(
)
2
−
1
=
0
(
8
)
T
h
e
p
ea
k
-
to
-
p
ea
k
v
alu
e
o
f
th
e
s
ig
n
al
g
iv
en
in
(
9
)
,
r
e
p
r
ese
n
ts
th
e
r
a
n
g
e
o
f
v
a
r
iatio
n
s
.
T
h
e
p
o
wer
q
u
ality
ev
en
ts
im
p
ac
t
o
n
s
u
c
h
v
ar
iatio
n
s
.
(
−
)
=
ma
x
{
(
)
}
−
min
{
(
)
}
,
∈
(
9
)
W
h
er
e
T
: 2
0
m
s
tim
e
win
d
o
w
is
co
n
s
id
er
ed
.
R
o
o
t
m
ea
n
s
q
u
ar
e
(
R
MS)
v
alu
e
o
f
v
o
ltag
e
s
ig
n
al
is
an
o
th
er
m
ea
s
u
r
e
o
f
t
h
e
m
ag
n
itu
d
e
v
a
r
iatio
n
an
d
f
o
u
n
d
u
s
ef
u
l f
o
r
elec
tr
ical
s
y
s
tem
b
eh
av
i
o
r
an
aly
s
is
[
2
8
]
.
R
MS
is
g
iv
en
in
(
10
).
=
√
1
∑
(
)
=
1
2
(
10
)
Me
an
ab
s
o
lu
te
d
ev
iatio
n
(
MA
D)
ass
ess
th
e
v
ar
iab
ilit
y
o
f
th
e
v
o
ltag
e
s
ig
n
al
h
elp
f
u
l
f
o
r
e
v
e
n
t
d
etec
tio
n
.
MA
D
is
f
o
r
m
u
lated
in
(
11
)
.
=
1
∑
|
(
)
−
|
=
1
(
11
)
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.
1
6
,
No
.
1
,
Feb
r
u
ar
y
20
2
6
:
10
-
24
18
4
.
4
.
Cla
s
s
if
ica
t
io
n by
s
up
po
rt
v
ec
t
o
r
ma
chine
Su
p
p
o
r
t
v
ec
to
r
m
ac
h
in
e
(
SV
M)
is
a
p
o
wer
f
u
l
m
ac
h
in
e
lear
n
in
g
m
o
d
el
u
s
ed
f
o
r
class
if
icatio
n
.
SVM
wo
r
k
s
b
y
f
in
d
in
g
th
e
o
p
tim
al
h
y
p
er
p
lan
e
th
at
b
est
s
ep
ar
ates
d
ata
in
to
d
if
f
er
e
n
t
class
es.
T
o
r
ed
u
ce
th
e
n
ee
d
o
f
lar
g
e
d
ata
s
ets
SVM
h
as
b
ee
n
p
r
ef
er
r
ed
o
v
e
r
ANN
an
d
DL
,
r
ed
u
ce
d
c
o
m
p
u
tatio
n
tim
e
an
d
clea
r
ly
v
is
ib
le
d
ec
is
io
n
b
o
u
n
d
ar
ies ar
e
t
h
e
ad
d
ed
ad
v
an
tag
es o
f
SVM.
I
n
th
e
co
n
tex
t
o
f
is
lan
d
in
g
d
e
tectio
n
,
SVM
is
tr
ain
ed
o
n
f
e
atu
r
es
ex
tr
ac
ted
f
r
o
m
v
o
ltag
e
d
ata.
T
h
e
weig
h
ts
(
w
)
o
f
ea
ch
f
ea
tu
r
e
c
o
n
tr
ib
u
te
i
n
d
eter
m
i
n
in
g
th
e
d
ec
is
io
n
b
o
u
n
d
ar
ies
wh
ich
a
r
e
lear
n
ed
b
y
m
ac
h
i
n
e
d
u
r
in
g
tr
ain
in
g
t
o
m
ax
im
ize
d
is
tan
ce
b
etwe
en
th
e
h
y
p
e
r
p
lan
e
an
d
s
u
p
p
o
r
t
v
ec
t
o
r
s
.
T
h
e
b
i
as
(
b
)
p
o
s
itio
n
s
th
e
h
y
p
er
p
lan
e
o
p
tim
ally
,
in
ca
s
e
d
ata
is
n
o
t
ce
n
ter
ed
o
n
o
r
ig
in
.
T
h
e
d
ec
is
io
n
f
u
n
ctio
n
is
d
ef
i
n
ed
as
in
(
1
2
)
wh
er
e
‘
x
’
is
th
e
f
ea
tu
r
e
v
alu
e.
(
)
=
(
,
)
+
(1
2
)
T
h
e
SVM
class
if
ies th
e
ev
en
ts
as is
lan
d
in
g
if
(
)
≥
0
an
d
as n
o
n
is
lan
d
in
g
if
(
)
<
0
.
Fo
llo
win
g
ar
e
th
e
s
tep
s
in
v
o
lv
ed
in
SVM
alg
o
r
ith
m
.
Step
1:
Featu
r
e
v
ec
to
r
in
itializatio
n
=
[
1
,
2
,
.
.
.
,
]
an
d
L
a
b
els
=
[
1
,
2
]
h
av
e
b
ee
n
s
et
as
1
an
d
-
1
in
d
icatin
g
th
e
class
,
s
u
f
f
ix
‘
’
r
ef
er
s
to
s
am
p
le
n
u
m
b
er
.
T
h
e
h
y
p
er
p
lan
e
is
f
o
r
m
u
lated
as in
(
1
3
)
.
+
=
0
(1
3
)
Step
2
:
Ma
r
g
in
m
ax
im
izatio
n
is
ac
h
iev
ed
b
y
(
1
4
)
,
m
ar
g
in
.
.
th
e
d
is
tan
ce
b
etwe
en
th
e
two
class
b
o
u
n
d
ar
ies
is
d
ef
in
ed
in
(
1
5
)
ᵢ
(
w
x
ᵢ
+
)
≥
1
(1
4
)
M
a
r
gin
=
2
|
|
w
|
|
(1
5
)
Step
3
: O
p
tim
al
v
alu
es o
f
an
d
ar
e
o
b
tain
ed
i
n
s
u
ch
a
way
th
at
|
|
|
|
r
esu
lts
in
to
m
in
im
u
m
as d
escr
ib
ed
in
(1
6
)
,
t
h
is
en
s
u
r
es m
ax
im
u
m
m
ar
g
in
s
atis
f
y
in
g
(
1
4
)
a
n
d
(
1
5
).
min
,
1
2
∥
∥
2
(1
6
)
Step
4
:
I
t
is
n
o
w
tr
ea
ted
as
d
u
al
o
b
jectiv
e
p
r
o
b
lem
n
am
ely
f
o
r
m
a
x
im
u
m
m
ar
g
in
an
d
u
n
b
iased
h
y
p
e
r
p
lan
e
r
ef
er
r
in
g
to
L
ag
r
an
g
ia
n
d
escr
i
b
ed
in
(
1
7
)
.
(
,
,
)
=
1
2
|
|
|
|
²
−
∑
ᵢ
[
ᵢ
(
w
X
ᵢ
+
)
−
1
]
=
1
(1
7
)
Par
tial
d
er
iv
ativ
es
o
f
L
ag
r
an
g
ian
w.
r
.
t
g
iv
es
o
p
tim
al
weig
h
ts
wh
ich
is
lin
ea
r
co
m
b
in
atio
n
o
f
th
e
tr
ain
in
g
s
am
p
les
v
ec
to
r
an
d
e
q
u
atin
g
it
to
ze
r
o
d
eter
m
in
es
weig
h
t
v
alu
es
f
o
r
ea
ch
f
ea
t
u
r
e
d
escr
ib
ed
in
(1
8
)
.
T
h
e
ex
p
r
ess
io
n
(
1
9
)
lead
s
to
an
u
n
b
iased
h
y
p
e
r
p
lan
e
f
o
r
th
e
two
class
es.
w
=
0
⇒
w
=
∑
ᵢ
ᵢ
ᵢ
=
1
(1
8
)
b
=
0
⇒
∑
ᵢ
ᵢ
=
1
=
0
(1
9
)
Su
b
s
titu
tin
g
in
to
th
e
L
a
g
r
an
g
i
an
th
e
d
u
al
o
p
tim
izatio
n
p
r
o
b
l
em
is
f
o
r
m
u
lated
as in
(
20
)
an
d
(
21
)
.
ma
x
=
∑
ⁿ
ᵢ
₌₁
ᵢ
−
1
2
∑
ᵢ
ⱼ
ᵢ
ⱼ
X
ᵢ
ᵀ
Xⱼ
,
=
1
(
20
)
ᵢ
≥
0
,
∑
ᵢ
ᵢ
=
1
=
0
(
21
)
Step
5
:
Ob
tain
i
n
g
α
ᵢ
u
s
in
g
q
u
a
d
r
atic
p
r
o
g
r
a
m
m
in
g
s
o
lv
er
s
a
n
d
id
e
n
tify
in
g
s
u
p
p
o
r
t
v
ec
to
r
s
(
).
C
o
m
p
u
tatio
n
o
f
weig
h
ts
(
)
is
d
escr
ib
ed
in
(
2
2
)
an
d
th
at
o
f
b
ias
(
)
f
o
r
s
u
p
p
o
r
t v
ec
to
r
x
ₖ
is
f
o
r
m
u
lated
in
(
2
3
)
.
=
∑
ᵢ
ᵢ
ᵢ
∈
(2
1
)
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
Dete
ctio
n
o
f isl
a
n
d
in
g
u
s
in
g
e
mp
ir
ica
l m
o
d
e
d
ec
o
mp
o
s
itio
n
a
n
d
…
(
B
a
lw
a
n
t P
a
til
)
19
=
ₖ
−
ₖ
(2
2
)
Step
6
:
Fu
n
ctio
n
in
(
2
4
)
is
u
s
ed
f
o
r
class
if
icatio
n
,
as
is
lan
d
in
g
(
+1
)
if
(
)
≥
0
an
d
n
o
n
-
is
lan
d
in
g
(
-
1
)
if
(
)
<0
.
(
)
=
+
(2
4
)
5.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
d
etec
tio
n
ac
c
u
r
ac
y
an
d
p
r
ed
ictio
n
tim
e
a
r
e
th
e
p
a
r
a
m
eter
s
o
f
p
r
im
a
r
y
in
ter
est
in
th
is
s
tu
d
y
.
Ob
tain
ed
d
ata
s
ets
h
as
b
ee
n
u
s
ed
in
7
d
if
f
er
en
t
ap
p
r
o
ac
h
es
n
am
ed
as
Me
th
o
d
-
1
to
M
eth
o
d
-
7
.
All
th
ese
m
eth
o
d
s
ar
e
d
escr
ib
ed
in
th
e
f
o
llo
win
g
p
a
r
ag
r
a
p
h
s
.
T
a
b
le
3
d
etails
th
e
d
etec
tio
n
ac
cu
r
ac
y
an
d
p
r
ed
ictio
n
tim
e
f
o
r
Me
th
o
d
-
1
t
o
Me
th
o
d
-
7
a
n
d
Fig
u
r
e
7
g
iv
es d
etec
tio
n
ac
c
u
r
ac
y
co
m
p
ar
is
o
n
.
T
ab
le
3
.
C
lass
if
icatio
n
r
esu
lts
M
e
t
h
o
d
D
a
t
a
a
n
d
f
e
a
t
u
r
e
s
u
se
d
f
o
r
c
l
a
ss
i
f
i
c
a
t
i
o
n
M
L
Te
c
h
n
i
q
u
e
A
c
c
u
r
a
c
y
D
e
t
e
c
t
i
o
n
t
i
m
e
D
e
t
e
c
t
i
o
n
Ti
me
w
i
t
h
I
M
F
1
e
x
t
r
a
c
t
i
o
n
t
i
m
e
M
e
t
h
o
d
1
P
h
a
se
v
o
l
t
a
g
e
s (V
A
, V
B
, V
C
)
D
e
c
i
s
i
o
n
Tr
e
e
7
0
.
4
1
%
1
.
9
ms
6
3
.
7
7
m
s
M
e
t
h
o
d
2
R
a
n
d
o
m F
o
r
e
s
t
7
1
.
4
6
%
8
8
.
7
1
ms
1
5
0
.
5
8
ms
M
e
t
h
o
d
3
I
M
F
1
o
f
p
h
a
se
A
(
4
f
e
a
t
u
r
e
s)
S
V
M
m
o
d
e
l
8
4
.
6
0
%
3
.
3
1
ms
6
5
.
1
8
m
s
M
e
t
h
o
d
4
I
M
F
1
o
f
a
l
l
3
p
h
a
s
e
s (4
f
e
a
t
u
r
e
s)
S
V
M
m
o
d
e
l
9
4
.
8
0
%
3
.
5
0
ms
6
5
.
3
7
m
s
M
e
t
h
o
d
5
I
M
F
1
o
f
p
h
a
se
A
(
9
f
e
a
t
u
r
e
s)
S
V
M
m
o
d
e
l
9
7
.
6
0
%
1
.
3
1
ms
6
3
.
1
8
m
s
M
e
t
h
o
d
6
A
v
e
r
a
g
e
o
f
I
M
F
1
o
f
3
p
h
a
se
v
o
l
t
a
g
e
s
S
V
M
m
o
d
e
l
9
9
.
8
%
1
.
2
4
mse
c
6
3
.
1
1
m
s
M
e
t
h
o
d
7
I
M
F
1
o
f
a
l
l
3
p
h
a
s
e
s (2
7
f
e
a
t
u
r
e
s)
S
V
M
m
o
d
e
l
9
9
.
4
%
1
.
4
2
mse
c
6
3
.
2
9
m
s
Fig
u
r
e
7
.
Dete
ctio
n
ac
c
u
r
ac
y
c
o
m
p
ar
is
o
n
o
f
d
if
f
er
en
t
m
eth
o
d
s
I
n
Me
th
o
d
-
1
an
d
Me
th
o
d
-
2
,
p
h
ase
v
o
ltag
es n
am
ely
V
A
,
V
B
,
an
d
V
C
in
th
e
f
o
r
m
o
f
tim
e
s
er
ies d
ata
h
as
b
ee
n
u
s
ed
f
o
r
class
if
icatio
n
,
t
h
e
o
r
ig
in
al
f
o
r
m
o
f
th
e
s
ig
n
al
is
u
s
ed
with
o
u
t
an
y
d
ec
o
m
p
o
s
itio
n
.
DT
an
d
R
F
ML
tech
n
iq
u
es
ar
e
u
s
ed
f
o
r
cl
ass
if
y
in
g
th
e
ev
en
ts
an
d
it
is
f
o
u
n
d
t
h
at
d
etec
tio
n
ac
c
u
r
ac
y
is
as
lo
w
as
7
0
.
4
1
%
wh
ich
is
n
o
t
s
atis
f
ac
to
r
y
.
T
o
ex
am
in
e
th
e
s
ig
n
if
ican
ce
o
f
s
ig
n
al
d
ec
o
m
p
o
s
itio
n
,
in
Me
t
h
o
d
-
3
th
e
I
MF
1
o
f
p
h
ase
v
o
ltag
e
V
A
g
en
er
ated
b
y
E
MD
h
as
b
ee
n
u
s
ed
.
Her
e
f
o
u
r
f
ea
tu
r
es
n
am
ely
Me
a
n
,
SD,
E
n
er
g
y
an
d
T
HD
o
f
I
MF
1
of
V
A
h
as
b
ee
n
c
o
n
s
id
er
ed
f
o
r
class
if
icatio
n
u
s
in
g
SVM
tech
n
iq
u
e,
th
o
u
g
h
o
n
ly
o
n
e
p
h
ase
d
ata
is
u
s
ed
ac
cu
r
ac
y
h
as in
cr
ea
s
ed
to
8
4
.
6
0
% wh
ich
is
s
ig
n
if
ican
t c
o
m
p
ar
e
to
Me
th
o
d
-
1
an
d
Me
th
o
d
-
2
.
C
o
n
s
id
er
atio
n
o
f
o
n
ly
o
n
e
p
h
ase
d
ata
ca
n
n
o
t
b
e
g
en
er
alize
d
s
in
ce
r
esu
ltin
g
ev
en
ts
im
p
a
cts
all
th
r
ee
p
h
ases
.
T
h
er
ef
o
r
e,
in
Me
th
o
d
-
4
ab
o
v
e
m
en
tio
n
e
d
f
ea
tu
r
es
o
f
I
MF
1
o
f
all
3
-
p
h
ase
v
o
lta
g
es
n
am
ely
V
A
,
V
B
,
an
d
V
C
ar
e
u
s
ed
an
d
class
if
icatio
n
is
o
b
s
er
v
ed
u
s
in
g
SVM.
Acc
u
r
ac
y
in
t
h
is
ca
s
e
h
as
in
cr
ea
s
ed
alm
o
s
t
b
y
1
0
%
co
m
p
ar
e
to
Me
th
o
d
-
3
i.e
.
4
7
4
ev
en
ts
ar
e
co
r
r
ec
tly
d
etec
ted
r
esu
ltin
g
in
an
ac
cu
r
ac
y
o
f
9
4
.
8
0
%.
T
o
ch
ec
k
th
e
im
p
ac
t
o
f
ad
d
iti
o
n
al
s
tatical
f
ea
tu
r
es
Me
th
o
d
-
5
u
s
es
n
in
e
f
e
atu
r
es
f
o
r
I
MF
1
o
f
o
n
ly
V
A
n
am
ely
Me
a
n
,
SD,
Sk
ewn
ess
,
Ku
r
to
s
is
,
E
n
er
g
y
,
T
HD,
R
MS,
p
ea
k
to
p
ea
k
v
alu
e
an
d
MA
D
.
Me
th
o
d
-
7
co
n
s
id
er
s
all
th
ese
f
ea
tu
r
es
f
o
r
I
MF
1
o
f
V
A
,
V
B
,
an
d
V
C
m
ak
i
n
g
a
la
r
g
e
d
ata
s
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De
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