I
nd
o
ne
s
ia
n J
o
urna
l o
f
E
lect
rica
l En
g
ineering
a
nd
Co
m
pu
t
er
Science
Vo
l.
39
,
No
.
1
,
J
u
l
y
2
0
2
5
,
p
p
.
101
~
1
0
9
I
SS
N:
2
5
0
2
-
4
7
5
2
,
DOI
: 1
0
.
1
1
5
9
1
/ijeecs.v
39
.i
1
.
p
p
1
0
1
-
1
0
9
101
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ee
cs.ia
esco
r
e.
co
m
Ra
ndo
m forest
m
ethod for
predic
ti
ng
discha
rg
e curr
ent
wa
v
eform a
nd m
o
de of diele
ctric
b
a
rrier
discha
rg
es
L
a
ia
di Abdel
ha
m
id
1
,
Chent
o
uf
Abdella
h
1
,
E
zz
iy
y
a
ni M
o
s
t
a
f
a
2
1
La
b
o
r
a
t
o
r
y
o
f
a
p
p
l
i
e
d
p
h
y
s
i
c
s
,
P
h
y
s
i
c
s De
p
a
r
t
me
n
t
,
F
S
TT,
U
A
E
U
n
i
v
e
r
s
i
t
y
,
Ta
n
g
i
e
r
,
M
o
r
o
c
c
o
2
M
a
t
h
e
ma
t
i
c
s
a
n
d
A
p
p
l
i
c
a
t
i
o
n
La
b
o
r
a
t
o
r
y
,
F
S
T
T,
U
A
E
U
n
i
v
e
r
si
t
y
,
T
a
n
g
i
e
r
,
M
o
r
o
c
c
o
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
May
25
,
2
0
2
4
R
ev
is
ed
J
an
17
,
2
0
2
5
Acc
ep
ted
Mar
25
,
2
0
2
5
Th
is
stu
d
y
a
d
d
re
ss
e
s
th
e
c
las
sifica
ti
o
n
o
f
Ho
m
o
g
e
n
e
o
u
s
a
n
d
F
i
lam
e
n
tary
d
isc
h
a
rg
e
m
o
d
e
s
in
d
iele
c
tri
c
b
a
rrier
d
isc
h
a
rg
e
(DBD
)
sy
ste
m
s
a
n
d
p
re
d
icts
th
e
Ho
m
o
g
e
n
e
o
u
s
c
u
rre
n
t
wa
v
e
fo
rm
u
si
n
g
m
a
c
h
in
e
lea
rn
in
g
(
M
L).
Th
e
m
o
ti
v
a
ti
o
n
ste
m
s
fro
m
th
e
n
e
e
d
fo
r
a
c
c
u
ra
te
m
o
d
e
ll
i
n
g
in
n
o
n
-
th
e
rm
a
l
p
las
m
a
sy
ste
m
s.
Th
e
p
r
o
b
lem
tac
k
led
is
d
isti
n
g
u
is
h
in
g
b
e
twe
e
n
th
e
se
tw
o
m
o
d
e
s
a
n
d
p
re
d
ictin
g
th
e
c
u
rre
n
t
wa
v
e
fo
rm
fo
r
Ho
m
o
g
e
n
e
o
u
s
d
isc
h
a
rg
e
.
A
ra
n
d
o
m
fo
re
st
c
las
sifica
ti
o
n
a
lg
o
rit
h
m
is
a
p
p
l
ied
,
u
si
n
g
e
x
p
e
rime
n
tal
fe
a
tu
re
s
su
c
h
a
s
a
p
p
li
e
d
v
o
lt
a
g
e
,
fre
q
u
e
n
c
y
,
g
a
s
g
a
p
,
d
iele
c
tri
c
m
a
teria
l,
a
n
d
g
a
s
ty
p
e
.
An
e
x
p
o
n
e
n
ti
a
l
m
o
d
e
l
is
p
ro
p
o
se
d
fo
r
t
h
e
d
isc
h
a
rg
e
c
u
r
re
n
t,
wit
h
G
a
u
ss
ian
re
g
re
ss
io
n
tran
sfo
rm
in
g
th
e
m
o
d
e
l
’
s
p
a
ra
m
e
ters
.
Th
e
c
las
sifica
ti
o
n
re
su
lt
s
a
re
e
v
a
lu
a
te
d
t
h
ro
u
g
h
a
c
o
n
f
u
sio
n
m
a
tri
x
,
sh
o
wc
a
sin
g
8
0
%
a
c
c
u
ra
c
y
in
d
isti
n
g
u
ish
in
g
d
isc
h
a
rg
e
m
o
d
e
s.
Th
e
re
g
re
ss
io
n
a
n
a
ly
sis
re
v
e
a
ls
stro
n
g
P
e
a
rso
n
c
o
rre
lati
o
n
c
o
e
fficie
n
t
s
b
e
twe
e
n
p
re
d
icte
d
a
n
d
e
x
p
e
rime
n
tal
wa
v
e
fo
rm
s.
In
c
o
n
c
l
u
sio
n
,
t
h
e
re
su
lt
s
d
e
m
o
n
stra
te
th
e
e
ffica
c
y
o
f
M
L
tec
h
n
iq
u
e
s
in
e
n
h
a
n
c
i
n
g
DBD
sy
ste
m
m
o
d
e
ll
in
g
,
t
h
o
u
g
h
imp
r
o
v
e
m
e
n
ts
c
a
n
b
e
m
a
d
e
b
y
e
x
p
a
n
d
in
g
t
h
e
d
a
tas
e
t
a
n
d
re
fin
in
g
fe
a
tu
re
se
lec
ti
o
n
fo
r
b
e
tt
e
r
c
las
sifica
ti
o
n
a
n
d
p
re
d
icti
o
n
p
e
rfo
rm
a
n
c
e
.
K
ey
w
o
r
d
s
:
C
o
ld
atm
o
s
p
h
er
ic
p
lasma
Dielec
tr
ic
b
ar
r
ier
d
is
ch
ar
g
e
Fil
am
en
tar
y
m
o
d
e
Ho
m
o
g
en
e
o
u
s
m
o
d
e
Ma
ch
in
e
l
ea
r
n
in
g
R
an
d
o
m
f
o
r
est
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
L
aiad
i A
b
d
elh
am
id
L
ab
o
r
ato
r
y
o
f
ap
p
lied
p
h
y
s
ics,
Ph
y
s
ics De
p
ar
tm
en
t,
FS
T
T
,
UAE
Un
iv
er
s
ity
T
an
g
ier
,
Mo
r
o
cc
o
E
m
ail:
h
am
id
laiad
i@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
Dielec
tr
ic
b
ar
r
ier
d
is
ch
ar
g
e
(
DB
Ds),
also
k
n
o
wn
as
s
ilen
t
d
is
ch
ar
g
es,
ar
e
co
n
s
id
er
ed
th
e
s
im
p
lest
way
to
o
b
tain
n
o
n
-
th
er
m
al
p
l
asm
a
(
also
k
n
o
wn
as
co
ld
-
p
la
s
m
a)
in
th
e
lab
o
r
ato
r
y
at
atm
o
s
p
h
er
ic
p
r
ess
u
r
e.
T
o
p
r
ev
e
n
t
th
e
f
o
r
m
atio
n
o
f
a
n
elec
tr
ic
ar
c,
at
least
o
n
e
d
iel
ec
tr
ic
b
ar
r
ier
is
u
s
ed
b
etwe
en
cy
lin
d
r
ical
o
r
two
p
lan
ar
elec
tr
o
d
es,
wh
ich
ar
e
c
o
n
n
ec
ted
t
o
an
alter
n
ativ
e
o
r
p
u
ls
ed
p
o
wer
s
u
p
p
ly
[
1
]
.
DB
Ds
h
av
e
n
u
m
e
r
o
u
s
ap
p
licatio
n
s
in
th
e
d
o
m
ain
s
o
f
in
d
u
s
tr
y
[
2
]
,
m
e
d
icin
e
[
3
]
,
a
n
d
en
v
ir
o
n
m
en
t
[
4
]
.
D
B
Ds
h
a
v
e
t
w
o
m
o
d
es
,
H
o
m
o
g
e
n
e
o
u
s
a
n
d
F
i
la
m
e
n
t
a
r
y
.
T
h
e
H
o
m
o
g
e
n
o
u
s
d
is
c
h
a
r
g
e
m
o
d
e
i
s
t
y
p
i
c
a
l
l
y
p
r
o
d
u
c
e
d
w
h
e
n
g
a
s
e
s
s
u
c
h
a
s
H
e
l
i
u
m
,
N
e
o
n
,
A
r
g
o
n
a
r
e
u
s
e
d
[
5
]
.
G
e
n
e
r
a
l
l
y
,
t
h
e
c
u
r
r
e
n
t
w
a
v
e
f
o
r
m
o
f
H
o
m
o
g
e
n
e
o
u
s
d
i
s
c
h
a
r
g
e
is
ch
a
r
a
c
t
e
r
i
z
e
d
b
y
a
s
i
n
g
l
e
p
u
l
s
e
i
n
e
a
c
h
h
a
l
f
c
y
c
l
e
o
f
t
h
e
ap
p
l
i
e
d
v
o
l
t
a
g
e
,
t
h
e
h
o
m
o
g
e
n
o
u
s
d
i
s
c
h
a
r
g
e
m
o
d
e
m
a
y
m
a
n
i
f
e
s
t
as
At
m
o
s
p
h
e
r
i
c
p
r
e
s
s
u
r
e
g
l
o
w
d
is
c
h
a
r
g
e
(
AP
GD
)
o
r
A
t
m
o
s
p
h
e
r
ic
p
r
e
s
s
u
r
e
T
o
w
n
s
e
n
d
d
i
s
c
h
a
r
g
e
(
A
P
T
D
)
[
6
]
,
s
e
v
e
r
a
l
f
a
c
t
o
r
s
c
o
u
l
d
i
n
f
l
u
e
n
c
e
t
h
e
w
a
v
e
f
o
r
m
o
f
th
e
H
o
m
o
g
e
n
e
o
u
s
d
i
s
c
h
a
r
g
e
c
u
r
r
e
n
t
i
n
D
B
D
c
o
n
f
i
g
u
r
a
t
i
o
n
a
s
s
h
o
w
n
i
n
F
i
g
u
r
e
1
,
i
n
c
l
u
d
i
n
g
t
h
e
a
p
p
l
i
e
d
v
o
l
t
a
g
e
[
7
]
,
t
h
e
f
r
e
q
u
e
n
c
y
o
f
t
h
e
a
p
p
l
i
e
d
v
o
l
t
a
g
e
[
8
]
,
t
h
e
g
a
s
t
y
p
e
[
9
]
,
t
h
e
g
a
s
g
a
p
d
is
ta
n
ce
[
1
0
]
,
a
n
d
t
h
e
d
i
e
l
e
c
t
r
i
c
m
a
t
e
r
ia
l
[
1
1
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
39
,
No
.
1
,
J
u
ly
20
25
:
101
-
1
0
9
102
Fig
u
r
e
1
.
Dielec
tr
ic
b
ar
r
ier
d
is
ch
ar
g
e
co
n
f
ig
u
r
atio
n
I
n
o
th
er
h
a
n
d
th
e
f
ilam
en
tar
y
d
is
ch
ar
g
e
m
o
d
e
is
th
e
m
o
s
t
n
atu
r
ally
o
cc
u
r
r
ed
in
DB
D
d
is
ch
ar
g
es
,
ty
p
ically
p
r
o
d
u
c
ed
i
n
Air
,
th
e
wav
ef
o
r
m
o
f
th
e
d
is
ch
ar
g
e
c
u
r
r
en
t
is
ch
ar
ac
ter
ized
b
y
r
a
n
d
o
m
f
lu
ctu
atio
n
s
d
escr
ib
e
th
e
r
an
d
o
m
d
is
tr
ib
u
tio
n
o
f
m
icr
o
-
d
is
ch
ar
g
es
in
s
p
a
ce
an
d
tim
e
[
9
]
.
I
n
th
is
wo
r
k
we
aim
to
p
r
ed
ict
th
e
d
is
ch
ar
g
e
m
o
d
e
o
f
DB
D
d
is
ch
ar
g
es
u
s
in
g
th
e
s
elec
ted
ex
p
er
im
en
tal
f
ea
t
u
r
es,
an
d
to
p
r
e
d
ict
th
e
d
is
ch
ar
g
e
cu
r
r
en
t w
a
v
ef
o
r
m
o
f
th
e
H
o
m
o
g
en
eo
u
s
m
o
d
e
.
Giv
en
th
e
a
b
u
n
d
an
t
e
x
p
er
im
en
tal
d
ata
g
en
er
ated
b
y
co
ld
p
lasma
an
d
DB
D
d
is
ch
ar
g
e
s
y
s
tem
s
,
a
r
ec
en
t
p
ar
a
d
ig
m
in
th
e
f
ield
o
f
co
ld
p
lasma
r
esear
ch
in
v
o
l
v
es
th
e
ad
o
p
tio
n
o
f
d
ata
-
d
r
i
v
e
n
m
o
d
ellin
g
[
1
2
]
.
Fo
r
ex
am
p
le
ML
m
eth
o
d
s
h
a
v
e
b
ee
n
em
p
lo
y
ed
to
p
r
e
d
ict
elec
tr
ical
ch
ar
ac
ter
is
t
ics
o
f
D
B
D
s
y
s
tem
s
[
1
3
]
,
an
d
s
im
u
late
t
h
e
lo
w
-
tem
p
er
at
u
r
e
p
lasma
[
1
4
]
.
E
x
p
l
o
it
in
g
t
h
e
d
iv
er
s
ity
o
f
cu
r
r
en
t
wav
ef
o
r
m
s
d
o
cu
m
en
ted
in
th
e
liter
atu
r
e
o
n
Ho
m
o
g
en
e
o
u
s
an
d
F
ilam
en
tar
y
DB
D
d
is
ch
ar
g
es,
o
u
r
s
tu
d
y
is
d
r
iv
en
b
y
two
m
ai
n
o
b
jectiv
es.
Fo
r
th
e
f
ir
s
t
o
b
jectiv
e,
we
aim
to
b
u
ild
a
m
o
d
el
to
class
if
y
th
e
d
is
ch
ar
g
e
m
o
d
e
u
s
in
g
th
e
r
an
d
o
m
f
o
r
est
class
if
icatio
n
alg
o
r
ith
m
,
th
e
s
ec
o
n
d
o
b
jectiv
e
in
v
o
lv
es
p
r
ed
ictin
g
th
e
d
is
ch
ar
g
e
cu
r
r
en
t
f
r
o
m
th
e
ex
p
er
im
en
tal
f
ea
tu
r
es
u
tili
zin
g
a
ML
al
g
o
r
ith
m
,
th
is
latter
o
b
jectiv
e
u
n
f
o
l
d
s
in
two
s
tep
s
:
f
ir
s
tly
,
we
aim
to
ass
o
ciate
th
e
ex
p
er
im
en
tal
f
e
atu
r
es
f
o
r
ea
c
h
cu
r
r
en
t
wa
v
e
f
o
r
m
with
a
s
et
o
f
d
ef
in
in
g
o
f
th
e
p
r
o
p
o
s
ed
Gau
s
s
ian
m
o
d
el
p
ar
am
eter
s
b
y
m
ed
iatin
g
th
e
p
r
o
p
o
s
ed
e
x
p
o
n
en
tial la
w
o
f
d
is
ch
ar
g
e.
Sec
o
n
d
ly
,
t
h
e
in
ten
tio
n
is
to
em
p
lo
y
a
r
an
d
o
m
f
o
r
s
t
r
eg
r
ess
io
n
m
o
d
el
to
p
r
e
d
ict
th
e
r
elatio
n
s
h
ip
b
etwe
en
ea
ch
p
ar
am
eter
o
f
th
e
d
is
ch
ar
g
e
cu
r
r
en
t m
o
d
el
an
d
t
h
e
ass
o
ciate
d
ex
p
er
im
en
tal
f
ea
tu
r
es.
T
h
e
o
u
tlin
e
o
f
t
h
is
p
ap
er
is
as
f
o
llo
ws:
f
ir
s
t
ly
,
th
e
d
ata
co
lle
ctio
n
p
r
o
ce
s
s
an
d
th
e
s
elec
ted
f
ea
tu
r
es
ar
e
d
escr
ib
ed
f
o
r
b
o
th
class
if
icatio
n
an
d
r
eg
r
ess
io
n
task
s
;
s
e
co
n
d
ly
,
th
e
class
if
ier
m
o
d
el
u
s
ed
to
class
if
y
th
e
d
is
ch
ar
g
e
m
o
d
e
o
f
th
e
DB
D
d
is
ch
ar
g
e
will b
e
d
escr
ib
ed
,
alo
n
g
wi
th
its
r
esu
lts
an
d
ev
alu
atio
n
.
Su
b
s
eq
u
e
n
tly
,
th
e
p
r
o
p
o
s
ed
m
o
d
el
f
o
r
th
e
d
is
ch
ar
g
e
c
u
r
r
en
t
will
b
e
s
u
g
g
ested
,
an
d
th
e
ex
tr
ac
tio
n
o
f
p
a
r
am
eter
s
f
o
r
r
eg
r
ess
io
n
will
b
e
i
n
tr
o
d
u
ce
d
.
Fo
llo
win
g
th
is
,
th
e
c
o
n
f
i
g
u
r
atio
n
an
d
ap
p
licatio
n
o
f
th
e
r
an
d
o
m
f
o
r
est
r
eg
r
ess
i
on
m
o
d
el
ar
e
d
escr
ib
e
d
,
an
d
t
h
e
r
esu
lts
d
er
iv
e
d
f
r
o
m
its
ap
p
licatio
n
ar
e
ev
alu
ate
d
.
2.
M
E
T
H
O
D
Fo
r
th
e
class
if
icatio
n
p
ar
t
t
h
e
d
ataset
was
co
llected
f
r
o
m
1
0
0
d
is
ch
ar
g
e
e
x
p
er
im
e
n
ts
,
an
d
f
o
r
th
e
r
eg
r
ess
io
n
p
ar
t,
it
was
s
o
u
r
ce
d
f
r
o
m
3
3
H
o
m
o
g
e
n
eo
u
s
DB
D
d
is
ch
ar
g
e
ex
p
e
r
im
en
ts
.
E
ac
h
d
is
ch
ar
g
e
c
u
r
r
e
n
t
wav
ef
o
r
m
was sam
p
led
in
to
1
,
0
0
0
p
o
in
ts
with
ass
o
ciate
d
d
ata
in
clu
d
in
g
ap
p
lied
v
o
ltag
e
a
m
p
litu
d
e,
f
r
e
q
u
en
c
y
o
f
th
e
ap
p
lied
v
o
ltag
e,
g
as
g
ap
,
g
as
ty
p
e,
an
d
d
ielec
tr
ic
m
ater
ial
u
s
ed
.
T
h
e
g
ases
em
p
lo
y
ed
in
th
is
wo
r
k
in
clu
d
e:
Air
[
8
]
-
[
1
1
]
,
[
1
5
]
,
[
1
6
]
,
Xen
o
n
[
1
7
]
,
Heliu
m
[
1
8
]
,
[
1
9
]
,
Ar
g
o
n
[
6
]
,
Nitr
o
g
e
n
[
6
]
,
[
2
0
]
,
an
d
Neo
n
[
9
]
,
[
2
1
]
.
T
h
e
g
eo
m
etr
ic
co
n
f
ig
u
r
atio
n
s
o
f
th
e
d
ielec
tr
ic
b
ar
r
ier
in
th
e
d
ataset
ar
e
b
o
th
p
lan
ar
an
d
c
y
lin
d
r
ical.
All
ex
p
er
im
en
ts
wer
e
co
n
d
u
cted
at
atm
o
s
p
h
e
r
ic
p
r
ess
u
r
e.
T
ab
le
1
illu
s
tr
ates
a
s
am
p
le
d
ex
am
p
le
f
o
r
th
e
s
tr
u
ctu
r
e
o
f
th
e
d
ata
co
llected
,
wh
ile
T
ab
le
2
p
r
o
v
id
es
a
s
tatis
t
ical
o
v
er
v
iew
o
f
th
e
ex
p
er
im
en
tal
f
ea
tu
r
e
v
alu
es
with
in
th
e
d
ataset.
T
ab
le
1
.
Stru
ctu
r
e
of
th
e
class
if
icatio
n
d
ata
A
u
t
h
o
r
V
o
l
t
a
g
e
(
k
V
)
F
r
e
q
u
e
n
c
y
(
k
H
z
)
G
a
p
(
mm
)
G
a
s
D
i
e
l
e
c
t
r
i
c
M
o
d
e
M
a
n
g
o
l
i
n
i
[
1
9
]
2
10
5
H
e
l
i
u
m
A
l
u
m
i
n
a
H
o
mo
g
e
n
e
o
u
s
G
a
r
a
mo
o
n
[
1
6
]
5
0
.
0
5
1
.
1
A
i
r
Q
u
a
r
t
z
F
i
l
a
m
e
n
t
a
r
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
R
a
n
d
o
m
fo
r
est me
th
o
d
fo
r
p
r
ed
ictin
g
d
is
ch
a
r
g
e
c
u
r
r
en
t wa
ve
fo
r
m
a
n
d
mo
d
e
…
(
La
ia
d
i A
b
d
elh
a
mid
)
103
T
ab
le
2
.
Statis
tic
v
alu
es o
f
th
e
f
ea
tu
r
es u
s
ed
in
class
if
icatio
n
V
o
l
t
a
g
e
(
k
V
)
F
r
e
q
u
e
n
c
y
(
k
H
z
)
G
a
p
(
mm
)
G
a
s B
r
e
a
k
d
o
w
n
(
k
V
/
mm
)
D
i
e
l
e
c
t
r
i
c
c
o
n
s
t
a
n
t
M
i
n
0
.
5
0
.
0
5
0
.
4
0
.
6
2
.
3
M
a
x
25
1
5
0
10
2
2
.
5
1
1
.
5
4
M
e
a
n
6
.
7
6
1
4
.
9
4
2
.
6
1
9
.
8
3
6
.
4
S
t
a
n
d
a
r
d
d
e
v
i
a
t
i
o
n
6
.
5
2
20
1
.
9
7
8
.
3
1
2
.
3
4
3.
CL
AS
SI
F
I
CAT
I
O
N
M
O
D
E
L
As
s
o
m
e
f
ea
tu
r
es
in
T
ab
le
1
ar
e
ca
te
g
o
r
ical,
e
n
co
d
i
n
g
b
ec
o
m
es
n
ec
ess
ar
y
.
Sp
ec
i
f
ically
,
th
e
d
ielec
tr
ic
m
ater
ial
was
en
co
d
ed
in
to
its
co
r
r
esp
o
n
d
in
g
d
iel
ec
tr
ic
co
n
s
tan
t,
wh
ile
th
e
g
as
ty
p
e
was
en
co
d
e
d
b
ased
o
n
its
av
er
ag
e
b
r
ea
k
d
o
wn
v
o
ltag
e
at
atm
o
s
p
h
er
ic
p
r
es
s
u
r
e.
Mo
r
eo
v
er
,
th
e
tar
g
et
v
alu
e,
r
ep
r
esen
tin
g
th
e
d
is
ch
ar
g
e
m
o
d
e,
was
en
co
d
ed
in
t
o
a
b
in
a
r
y
class
(
0
f
o
r
H
o
m
o
g
e
n
eo
u
s
a
n
d
1
f
o
r
F
ilam
en
tar
y
)
,
f
ac
ilit
atin
g
s
tr
ea
m
lin
ed
class
if
icatio
n
p
r
o
ce
s
s
es.
3
.
1
.
Ra
nd
o
m
f
o
re
s
t
f
o
r
cla
s
s
if
ica
t
io
n
A
m
ac
h
in
e
lear
n
i
n
g
a
p
p
r
o
ac
h
[
2
2
]
,
s
p
ec
if
ically
th
e
r
an
d
o
m
f
o
r
est
class
if
icatio
n
alg
o
r
it
h
m
[
2
3
]
is
ad
o
p
ted
to
p
r
ed
ict
an
d
m
o
d
el
th
e
in
h
e
r
en
tly
n
on
-
lin
e
ar
r
elatio
n
s
h
ip
b
etwe
en
th
e
d
i
s
ch
ar
g
e
m
o
d
e
an
d
ass
o
ciate
d
f
ea
tu
r
es
o
f
th
e
d
is
ch
ar
g
e
ex
p
e
r
im
en
t.
R
an
d
o
m
f
o
r
est
alg
o
r
ith
m
c
o
m
b
in
es
s
ev
er
al
d
ec
is
io
n
tr
ee
s
as
s
h
o
wn
in
Fig
u
r
e
2
to
cr
ea
te
a
m
o
r
e
ac
cu
r
ate
m
o
d
el
b
y
s
ele
ctin
g
r
an
d
o
m
s
u
b
s
ets
o
f
d
ata
an
d
f
ea
t
u
r
es,
th
e
n
ag
g
r
eg
atin
g
th
e
r
esu
lts
to
m
a
k
e
a
f
in
al
p
r
e
d
ictio
n
th
r
o
u
g
h
m
ajo
r
ity
v
o
tin
g
.
Fig
u
r
e
2
.
R
an
d
o
m
f
o
r
est cla
s
s
i
f
icatio
n
alg
o
r
ith
m
T
h
e
f
ea
tu
r
es
ch
o
s
en
f
o
r
class
if
icatio
n
ca
n
b
e
en
ca
p
s
u
lated
with
in
a
v
ec
to
r
X
c
=
[
Up
,
d
,
V
bd
,
ε
d
]
,
wh
er
e
U
p
d
en
o
te
t
h
e
ap
p
lied
v
o
ltag
e
am
p
litu
d
e,
d
th
e
g
as
g
ap
d
is
tan
ce
,
V
bd
th
e
b
r
ea
k
d
o
wn
v
o
ltag
e
o
f
th
e
g
as,
an
d
ε
d
d
en
o
te
th
e
m
ate
r
ial
d
ielec
tr
ic
co
n
s
tan
t.
T
h
e
tar
g
et
v
ec
to
r
is
d
e
n
o
ted
as
y
c
=
[
‘
Ho
m
o
g
en
e
o
u
s
’
,
‘
Fil
am
en
tar
y
’
]
.
Fo
r
th
e
r
an
d
o
m
f
o
r
est
class
if
ier
(
R
FC
)
alg
o
r
ith
m
,
th
e
c
h
o
s
en
h
y
p
er
p
a
r
a
m
eter
s
in
clu
d
e
th
e
n
u
m
b
er
o
f
tr
ee
s
(
n
_
esti
m
ato
r
s
=1
2
0
)
,
an
d
th
e
cr
iter
io
n
u
s
ed
is
‘
en
tr
o
p
y
’
.
T
h
e
t
r
ain
in
g
d
at
a
is
u
s
ed
to
tr
ai
n
th
e
class
if
ier
m
o
d
el
b
y
p
r
o
v
id
in
g
in
p
u
t
f
ea
tu
r
es
an
d
co
r
r
esp
o
n
d
in
g
tar
g
et
v
alu
es.
T
h
e
test
d
ata,
co
m
p
r
is
in
g
2
0
% o
f
th
e
t
o
tal
d
ataset,
is
r
eser
v
ed
to
e
v
alu
ate
h
o
w
well
th
e
tr
ain
ed
R
FC
p
er
f
o
r
m
s
o
n
n
ew
,
u
n
s
ee
n
d
ata
.
3
.
2
.
Cla
s
s
if
ica
t
io
n
re
s
ults a
nd
ev
a
lua
t
io
n
3
.
2
.
1
.
Co
nfusi
o
n
m
a
t
rix
A
co
n
f
u
s
io
n
m
atr
ix
p
r
o
v
id
e
s
an
o
v
er
v
iew
o
f
th
e
class
if
ier
’
s
p
er
f
o
r
m
a
n
ce
b
y
illu
s
tr
atin
g
th
e
p
r
ed
icted
class
es
ag
ain
s
t
th
e
ac
tu
al
o
n
es.
I
n
Fig
u
r
e
3
,
th
e
co
n
f
u
s
io
n
m
atr
ix
f
o
r
o
u
r
class
if
ier
is
p
r
e
s
en
ted
,
wh
ich
o
f
f
er
s
a
clea
r
v
is
u
aliza
tio
n
o
f
th
e
r
a
n
d
o
m
f
o
r
est
cl
ass
if
icatio
n
m
o
d
el
’
s
p
er
f
o
r
m
a
n
ce
b
y
co
m
p
ar
in
g
p
r
ed
icted
class
es
ag
ain
s
t
ac
tu
al
d
is
ch
ar
g
e
m
o
d
es.
I
n
th
is
m
atr
ix
,
th
e
r
o
ws
r
e
p
r
esen
t
t
h
e
ac
tu
al
d
is
ch
ar
g
e
m
o
d
es (
Ho
m
o
g
en
eo
u
s
o
r
Fil
a
m
en
tar
y
)
,
wh
ile
th
e
co
lu
m
n
s
r
ep
r
esen
t th
e
p
r
e
d
icted
m
o
d
es.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
39
,
No
.
1
,
J
u
ly
20
25
:
101
-
1
0
9
104
Fig
u
r
e
3
.
C
o
n
f
u
s
io
n
m
atr
i
x
o
f
th
e
class
if
icatio
n
m
o
d
el
3
.
2
.
2
.
M
o
del e
v
a
lua
t
io
n
a
nd
dis
cu
s
s
io
n
Acc
u
r
ac
y
in
class
if
icatio
n
m
o
d
els
is
a
m
etr
ic
th
at
m
ea
s
u
r
es
th
e
p
r
o
p
o
r
tio
n
o
f
co
r
r
ec
tly
p
r
ed
icte
d
in
s
tan
ce
s
am
o
n
g
all
in
s
tan
ce
s
in
th
e
d
ataset.
I
t
p
r
o
v
id
es
an
o
v
er
all
ass
ess
m
en
t
o
f
th
e
m
o
d
el
’
s
ab
ilit
y
to
co
r
r
ec
tly
class
if
y
d
if
f
e
r
en
t c
la
s
s
es o
r
ca
teg
o
r
ies.
Acc
u
r
ac
y
is
ca
lcu
lated
as f
o
llo
ws:
=
+
+
+
+
w
h
er
e
T
p
,
T
n
,
Fp
,
Fn
d
en
o
tes
tr
u
e
p
o
s
itiv
e,
tr
u
e
n
e
g
ativ
e,
f
alse
p
o
s
itiv
e,
an
d
f
alse
n
eg
ativ
e
r
esp
ec
tiv
ely
,
b
y
an
aly
s
in
g
th
is
co
n
f
u
s
io
n
m
atr
ix
,
f
o
r
e
x
am
p
le,
th
e
m
o
d
el
h
as
m
ad
e
3
f
alse
p
o
s
itiv
e
p
r
ed
ictio
n
s
,
i.e
.
,
it
h
as
p
r
ed
icted
th
e
p
r
esen
ce
o
f
3
d
i
s
ch
ar
g
es
with
H
o
m
o
g
en
eo
u
s
m
o
d
es,
wh
er
ea
s
in
r
ea
lity
th
ey
ar
e
F
ilam
en
tar
y
,
th
e
ac
cu
r
ac
y
o
f
o
u
r
class
if
icatio
n
m
o
d
el
is
0
.
8
.
Ach
iev
in
g
8
0
%
ac
c
u
r
ac
y
in
o
u
r
class
if
icatio
n
m
o
d
el
is
a
p
o
s
itiv
e
r
esu
lt,
b
u
t
it
i
s
ess
en
tial
to
ex
p
l
o
r
e
th
e
im
p
licatio
n
s
o
f
t
h
e
f
als
e
p
o
s
itiv
e
p
r
ed
ictio
n
s
.
T
h
e
m
is
class
if
icatio
n
o
f
Fil
am
en
tar
y
d
is
ch
ar
g
es
as
Ho
m
o
g
en
e
o
u
s
r
e
v
ea
ls
lim
itatio
n
s
in
th
e
m
o
d
el
’
s
ab
ilit
y
t
o
clea
r
ly
d
is
tin
g
u
is
h
b
etwe
en
th
e
two
m
o
d
es.
T
h
is
s
u
g
g
ests
th
at
th
e
m
o
d
el
’
s
s
en
s
itiv
ity
to
s
u
b
tle
d
if
f
er
en
ce
s
b
etwe
en
th
ese
d
i
s
ch
ar
g
e
ty
p
es
n
ee
d
s
im
p
r
o
v
em
e
n
t.
Fu
r
t
h
er
r
e
f
in
e
m
en
t
o
f
th
e
m
o
d
el,
p
ar
ticu
l
ar
ly
in
its
h
a
n
d
lin
g
o
f
n
u
a
n
ce
d
f
ea
tu
r
es,
co
u
ld
s
ig
n
if
ican
tly
en
h
a
n
ce
its
class
i
f
icatio
n
p
er
f
o
r
m
a
n
ce
.
4.
RE
G
RE
SS
I
O
N
M
O
D
E
L
4
.
1
.
P
r
o
po
s
ed
dis
cha
rg
e
curr
ent
m
o
del
T
h
e
d
is
ch
ar
g
e
cu
r
r
en
t
i
s
co
n
s
i
d
er
ed
as
an
i
n
ter
n
al
elec
tr
ical
p
ar
am
eter
o
f
DB
D,
it
lac
k
s
an
ex
p
licit
ex
p
r
ess
io
n
,
a
n
d
it
is
d
if
f
icu
lt
to
m
ea
s
u
r
e
it
d
ir
ec
tly
,
th
e
m
o
d
els
ad
d
r
ess
in
g
th
is
c
u
r
r
en
t
f
all
in
to
two
m
ain
ca
teg
o
r
ies:
p
h
y
s
ical
m
o
d
els,
wh
ich
em
p
lo
y
n
u
m
er
ical
s
im
u
latio
n
s
to
d
ed
u
ce
th
e
cu
r
r
en
t
wav
ef
o
r
m
[
2
4
]
an
d
elec
tr
ical
m
o
d
els
[
1
5
]
.
T
h
e
h
y
p
o
th
esis
o
f
th
is
wo
r
k
is
g
r
o
u
n
d
ed
o
n
th
e
s
im
p
le
elec
tr
ical
m
o
d
el
f
o
r
DB
D
,
as
illu
s
tr
ated
in
Fig
u
r
e
4
.
I
n
th
is
m
o
d
el,
C
d
an
d
C
g
d
en
o
te
th
e
d
ielec
tr
ic
b
ar
r
ier
ca
p
ac
ita
n
ce
an
d
g
as
g
a
p
ca
p
ac
itan
ce
,
r
esp
ec
tiv
ely
,
w
h
ile
R
p
r
ep
r
esen
ts
th
e
p
lasma
d
is
ch
ar
g
e
im
p
e
d
an
ce
(
Fig
u
r
e
4
(
a
)
)
[
2
5
]
.
T
h
e
p
r
o
p
o
s
ed
m
o
d
el
o
p
er
ate
s
u
n
d
er
ce
r
tain
ass
u
m
p
tio
n
s
:
Firstl
y
,
t
h
e
p
lasma
d
is
ch
ar
g
e
cu
r
r
e
n
t
I
plasma
(
t)
is
co
n
ce
p
tu
alize
d
as
th
e
ex
p
o
n
en
tial
law
as
in
eq
u
atio
n
(
1
)
(
Fig
u
r
e
4
(
b
)
)
.
Seco
n
d
l
y
,
we
s
u
p
p
o
s
e
th
at
th
e
d
is
ch
ar
g
e
cu
r
r
en
t
a
n
d
th
e
g
ap
v
o
ltag
e
wa
v
ef
o
r
m
s
ex
h
ib
i
ts
s
y
m
m
etr
y
with
r
esp
ec
t
to
th
e
h
alf
c
y
cle
o
f
th
e
alter
n
ativ
e
ap
p
lied
v
o
ltag
e.
T
h
e
m
o
d
el
I
(
t)
ad
o
p
ted
in
th
is
s
tu
d
y
is
a
m
o
d
if
ied
f
o
r
m
o
f
t
h
e
p
o
wer
law
[
2
5
]
wh
ich
ass
im
ilate
th
e
p
lasma
d
is
ch
ar
g
e
r
ea
ctan
ce
as a
s
em
i c
o
n
d
u
cto
r
d
ip
o
le.
(
)
=
(
(
)
−
1
)
(
1
)
=
(
2
+
α
)
(
2
)
W
h
er
e,
I
s
th
e
cu
r
r
e
n
t
am
p
litu
d
e
o
f
s
atu
r
atio
n
c
u
r
r
e
n
t,
V
g
is
th
e
v
o
ltag
e
ac
r
o
s
s
th
e
p
lasma
r
ea
ctan
ce
-
as
in
(
2
)
-
also
k
n
o
wn
as
g
ap
v
o
ltag
e,
n
is
a
s
ca
le
f
ac
to
r
,
V
m
th
e
a
m
p
litu
d
e
o
f
th
e
g
ap
v
o
lta
g
e,
f
th
e
f
r
eq
u
e
n
cy
o
f
th
e
g
ap
v
o
ltag
e
(
wh
ic
h
is
eq
u
al
to
th
e
ap
p
lied
v
o
ltag
e
f
r
eq
u
en
cy
)
,
α
r
e
p
r
esen
ts
th
e
p
h
ase
o
f
th
e
g
ap
v
o
lta
g
e,
an
d
m
it
is
a
co
r
r
ec
tio
n
v
alu
e
t
h
at
ac
co
u
n
ts
f
o
r
t
h
e
m
em
o
r
y
e
f
f
ec
t
in
th
e
s
ec
o
n
d
c
y
cle
o
f
th
e
ap
p
lied
v
o
ltag
e
.
T
h
is
m
em
o
r
y
ef
f
ec
t
ar
is
es
f
r
o
m
r
esid
u
al
c
h
ar
g
es
lef
t
f
r
o
m
t
h
e
p
r
ec
e
d
in
g
h
alf
p
er
io
d
[
1
5
]
,
(
m
=1
f
o
r
th
e
f
ir
s
t
cy
cle,
an
d
2
<m
<2
.
5
5
f
o
r
t
h
e
s
ec
o
n
d
c
y
cle)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
R
a
n
d
o
m
fo
r
est me
th
o
d
fo
r
p
r
ed
ictin
g
d
is
ch
a
r
g
e
c
u
r
r
en
t wa
ve
fo
r
m
a
n
d
mo
d
e
…
(
La
ia
d
i A
b
d
elh
a
mid
)
105
(
a)
(
b
)
Fig
u
r
e
4
.
E
lectr
ical
m
o
d
el
f
o
r
DB
D
(
a)
p
r
e
-
d
is
ch
ar
g
e
s
tate
an
d
(
b
)
d
is
ch
ar
g
e
p
h
ase
T
o
ex
tr
ac
t
th
e
p
ar
am
eter
s
o
f
th
e
p
r
o
p
o
s
ed
m
o
d
el,
an
in
itial
r
eg
r
ess
io
n
was
co
n
d
u
cted
u
s
in
g
th
e
ex
p
er
im
en
tal
d
is
ch
ar
g
e
d
ata
f
itted
to
th
e
e
x
p
o
n
en
tial
p
r
o
p
o
s
ed
m
o
d
el
I
(
t)
as
o
u
tlin
ed
in
e
q
u
atio
n
(
1
)
.
Fo
r
th
is
r
eg
r
ess
io
n
,
o
n
ly
h
al
f
o
f
th
e
p
er
i
o
d
o
f
t
h
e
Ho
m
o
g
en
eo
u
s
cu
r
r
en
t
wav
e
f
o
r
m
was
u
tili
ze
d
.
T
h
is
d
ec
is
io
n
s
tem
s
f
r
o
m
th
e
ass
u
m
p
tio
n
th
at
th
e
d
is
ch
ar
g
e
cu
r
r
en
t
wav
ef
o
r
m
ex
h
ib
its
s
y
m
m
etr
y
r
elativ
e
to
th
e
h
alf
-
p
er
io
d
o
f
t
h
e
alter
n
ativ
e
ap
p
lied
v
o
ltag
e.
Fig
u
r
e
5
illu
s
tr
ates
th
e
o
v
er
all
r
e
g
r
ess
io
n
p
r
o
ce
s
s
,
a
n
e
x
am
p
l
e
o
f
th
e
r
eg
r
ess
io
n
f
itti
n
g
is
ill
u
s
tr
ated
in
Fig
u
r
e
5
(
a)
[
1
9
]
,
an
d
th
e
r
esu
ltin
g
p
ar
am
eter
s
ex
tr
ac
ted
f
r
o
m
th
is
m
o
d
el
ar
e
p
r
esen
ted
in
T
ab
le
3
.
4
.
1
.
1
.
G
a
us
s
ia
n m
o
del a
nd
pa
ra
m
e
t
er
s
ex
t
ra
ct
i
o
n
T
h
e
ex
p
o
n
e
n
tial
m
o
d
el
ex
h
i
b
its
r
esem
b
lan
ce
to
a
Gau
s
s
ian
wav
e,
as
d
ep
icte
d
in
(
3
)
.
Ho
wev
er
,
its
p
ar
am
eter
s
d
o
n
o
t
in
h
er
e
n
tly
r
ef
lect
th
e
d
ef
in
in
g
tr
aits
o
f
a
Gau
s
s
ian
wav
e,
s
u
ch
as
ce
n
ter
o
r
wid
th
.
T
h
er
ef
o
r
e,
a
s
ec
o
n
d
ar
y
r
eg
r
e
s
s
io
n
to
th
e
ex
p
o
n
en
tial
m
o
d
el
was
co
n
d
u
cted
.
T
h
is
r
eg
r
e
s
s
io
n
m
ap
p
ed
th
e
p
ar
am
eter
s
o
f
th
e
e
x
p
o
n
en
tial
m
o
d
el,
n
am
ely
I
s
,
Vm
,
n
,
an
d
α
,
to
th
e
Gau
s
s
ian
p
ar
a
m
eter
s
A,
µ,
a
n
d
σ
,
as
illu
s
tr
ated
in
Fig
u
r
e
5
(
b
)
.
T
ab
l
e
3
p
r
e
s
en
ts
th
eir
co
r
r
esp
o
n
d
in
g
Gau
s
s
ian
p
ar
a
m
eter
s
,
wh
er
ein
φ
s
er
v
es
as
th
e
co
r
r
ec
tio
n
p
ar
am
eter
t
o
ac
co
u
n
t f
o
r
t
h
e
m
em
o
r
y
ef
f
ec
t.
G
(
µ
,
σ
)
=
A
e
xp
(
−
(
−
µ
)
)
(
3
)
(
a)
(
b
)
Fig
u
r
e
5
.
E
x
p
o
n
en
tial a
n
d
Gau
s
s
ian
r
eg
r
ess
io
n
s
(
a)
r
eg
r
ess
io
n
o
f
th
e
p
r
o
p
o
s
ed
ex
p
o
n
en
tia
l m
o
d
el
to
th
e
ex
p
er
im
en
tal
cu
r
r
en
t
d
is
ch
ar
g
e
an
d
(
b
)
ch
a
r
ac
ter
is
tics
o
f
th
e
Gau
s
s
ian
cu
r
r
en
t w
av
e
T
ab
le
3
.
E
x
am
p
le
o
f
co
r
r
esp
o
n
d
in
g
e
x
p
o
n
en
tial a
n
d
Gau
s
s
ian
m
o
d
el
p
ar
am
eter
s
A
u
t
h
o
r
U
p
(
K
V
)
F
(
k
H
z
)
d
(
mm
)
V
bd
ε
d
Is
Vm
n
α
m
A
µ
σ
φ
G
a
r
a
mo
o
n
[
1
6
]
3
0
.
0
5
1
.
1
3
9
0
.
3
8
2
6
3
.
8
4
1
2
6
0.
09
2
.
5
5
.
6
3
1
7
.
9
7
1
1
.
1
0
0
.
8
6
4
.
1
.
2
.
G
a
us
s
ia
n m
o
del e
v
a
lu
a
t
io
n
T
h
e
ev
alu
atio
n
o
f
Gau
s
s
ian
r
eg
r
ess
io
n
in
v
o
lv
ed
two
k
ey
m
etr
ics.
Firstl
y
,
th
e
av
e
r
ag
e
m
ea
n
ab
s
o
lu
te
er
r
o
r
(
AM
AE
)
was
co
m
p
u
ted
as
th
e
m
ea
n
a
b
s
o
lu
te
d
if
f
er
en
ce
b
etwe
en
th
e
e
x
p
er
im
en
tal
s
ig
n
al
cu
r
r
en
ts
an
d
th
eir
c
o
r
r
esp
o
n
d
in
g
Gau
s
s
ian
r
eg
r
ess
ed
wav
es.
Seco
n
d
l
y
,
th
e
av
e
r
ag
e
m
ea
n
s
q
u
ar
e
d
er
r
o
r
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
39
,
No
.
1
,
J
u
ly
20
25
:
101
-
1
0
9
106
(
AM
SE)
was
ca
lcu
lated
as
th
e
m
ea
n
o
f
s
q
u
ar
ed
d
if
f
er
en
ce
s
b
etwe
en
th
e
ex
p
e
r
im
en
tal
s
ig
n
al
cu
r
r
en
ts
an
d
th
eir
co
r
r
esp
o
n
d
in
g
Gau
s
s
ian
r
eg
r
ess
ed
wav
es.
Fig
u
r
e
6
s
h
o
ws
th
e
ca
lcu
lated
v
alu
es
o
f
th
ese
m
etr
ics.
No
tab
ly
,
m
ae
i
an
d
m
s
e
i
d
en
o
te
th
e
m
ea
n
a
b
s
o
lu
te
er
r
o
r
an
d
m
ea
n
s
q
u
a
r
ed
e
r
r
o
r
,
r
esp
ec
tiv
ely
,
b
etwe
en
th
e
i
-
th
ex
p
er
im
en
tal
cu
r
r
en
t
wav
e
an
d
its
co
r
r
esp
o
n
d
in
g
Gau
s
s
ian
m
o
d
el
wav
e.
Sp
ec
if
ically
,
th
e
AM
AE
was
f
o
u
n
d
to
b
e
0
.
3
8
,
wh
ile
t
h
e
AM
SE
was d
eter
m
in
ed
to
b
e
0
.
4
4
.
Fig
u
r
e
6
.
Valu
es o
f
m
ea
n
a
b
s
o
lu
te
an
d
s
q
u
a
r
ed
er
r
o
r
s
b
etwe
e
n
th
e
ex
p
er
im
en
tal
cu
r
r
en
ts
an
d
th
eir
Gau
s
s
ian
r
eg
r
ess
io
n
4
.
2
.
Ra
nd
o
m
f
o
re
s
t
re
g
re
s
s
io
n
I
n
r
a
n
d
o
m
f
o
r
est
r
eg
r
ess
io
n
,
p
r
ed
ictio
n
s
ar
e
d
er
iv
e
d
th
r
o
u
g
h
th
e
a
v
er
ag
in
g
o
f
o
u
tp
u
ts
f
r
o
m
m
u
ltip
le
d
ec
is
io
n
tr
ee
s
,
wh
ich
h
elp
s
m
itig
ate
in
d
iv
id
u
al
tr
ee
b
iases
an
d
en
h
an
ce
o
v
er
all
p
r
ed
ic
tiv
e
ac
cu
r
ac
y
.
T
h
e
f
ea
tu
r
e
v
ec
to
r
is
X
r
=
[
Up
,
F,
d
,
V
bd
, ε
d
]
,
an
d
th
e
tar
g
et
v
alu
e
is
y
r
=
[
A,
µ
,
σ
,
φ
]
.
Hy
p
er
p
ar
am
eter
s
s
elec
ted
f
o
r
th
e
R
an
d
o
m
Fo
r
estR
eg
r
ess
o
r
alg
o
r
ith
m
co
n
s
is
t
o
f
th
e
n
u
m
b
er
o
f
tr
ee
s
(
n
_
esti
m
ato
r
s
=
4
5
)
,
with
th
e
m
ea
n
s
q
u
ar
ed
er
r
o
r
(
‘
m
s
e
’
)
cr
iter
i
o
n
em
p
lo
y
e
d
f
o
r
o
p
tim
izatio
n
.
Fig
u
r
e
7
p
r
o
v
id
es
an
o
v
er
v
ie
w
o
f
th
e
p
r
o
ce
s
s
f
o
r
ex
tr
ac
tin
g
p
a
r
am
eter
s
f
r
o
m
th
e
d
is
ch
ar
g
e
d
ata.
I
n
i
tially
,
we
d
er
iv
e
t
h
e
p
ar
a
m
eter
s
o
f
t
h
e
ex
p
o
n
e
n
tial
m
o
d
el,
f
o
llo
wed
b
y
th
e
ex
tr
ac
tio
n
o
f
Gau
s
s
ian
p
ar
am
eter
s
.
T
h
ese
e
x
tr
ac
ted
p
a
r
am
eter
s
s
er
v
e
as
t
ar
g
et
v
alu
es
f
o
r
th
e
r
an
d
o
m
f
o
r
est r
e
g
r
ess
io
n
.
Fig
u
r
e
7
.
Ov
e
r
v
iew
o
f
p
ar
am
e
ter
ex
tr
ac
tio
n
a
n
d
s
ch
em
atic
s
tr
u
ctu
r
e
o
f
th
e
r
an
d
o
m
f
o
r
est m
o
d
el
4
.
3
.
Reg
re
s
s
io
n r
esu
lt
s
a
nd
ev
a
lua
t
io
n
Fig
u
r
e
8
d
e
p
icts
an
ex
am
p
le
o
f
th
e
r
an
d
o
m
f
o
r
est
r
eg
r
es
s
io
n
r
esu
lts
b
y
p
r
esen
tin
g
th
e
p
r
ed
icted
d
is
ch
ar
g
e
cu
r
r
en
t
wav
e
f
o
r
m
with
its
co
r
r
esp
o
n
d
in
g
ex
p
er
i
m
en
tal
d
is
ch
ar
g
e
c
u
r
r
en
t
wav
ef
o
r
m
f
r
o
m
t
h
e
test
d
ata
[
1
6
]
.
T
h
e
clo
s
e
alig
n
m
en
t
b
etwe
en
th
e
p
r
ed
icted
an
d
e
x
p
er
im
en
tal
c
u
r
v
es
d
em
o
n
s
tr
at
es
th
e
ef
f
ec
tiv
en
ess
o
f
th
e
t
r
ain
ed
m
o
d
el
i
n
ca
p
tu
r
in
g
th
e
u
n
d
er
ly
in
g
cu
r
r
en
t
c
h
ar
ac
ter
is
tics
.
T
h
is
co
m
p
ar
is
o
n
s
er
v
es
to
v
alid
ate
th
e
r
o
b
u
s
tn
ess
an
d
p
r
ed
ictiv
e
ca
p
ab
ilit
y
o
f
th
e
r
an
d
o
m
f
o
r
es
t a
p
p
r
o
ac
h
f
o
r
m
o
d
elin
g
d
is
ch
ar
g
e
p
h
e
n
o
m
e
n
a.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
R
a
n
d
o
m
fo
r
est me
th
o
d
fo
r
p
r
ed
ictin
g
d
is
ch
a
r
g
e
c
u
r
r
en
t wa
ve
fo
r
m
a
n
d
mo
d
e
…
(
La
ia
d
i A
b
d
elh
a
mid
)
107
Fig
u
r
e
8
.
E
x
p
er
im
e
n
tal
d
is
ch
a
r
g
e
cu
r
r
en
t w
av
ef
o
r
m
a
n
d
th
e
p
r
ed
icted
m
o
d
el
cu
r
r
en
t w
av
e
f
o
r
m
I
n
ev
alu
atin
g
th
e
r
esu
lts
o
f
th
e
p
r
ed
icted
c
u
r
r
e
n
ts
wav
ef
o
r
m
s
ag
ain
s
t
th
e
ex
p
er
im
en
t
al
co
u
n
ter
p
a
r
ts
,
th
e
Pear
s
o
n
co
r
r
elatio
n
co
ef
f
icie
n
t
was
em
p
lo
y
ed
to
m
ea
s
u
r
e
th
e
lin
ea
r
r
elatio
n
s
h
ip
b
etwe
en
th
e
ex
p
er
im
en
tal
d
is
ch
ar
g
e
cu
r
r
e
n
ts
an
d
th
eir
ass
o
ciate
d
p
r
ed
icted
cu
r
r
en
ts
f
o
r
th
e
test
d
ata.
T
ab
le
4
p
r
esen
ts
th
e
p
ea
r
s
o
n
co
r
r
elatio
n
c
o
ef
f
icien
t
(
PC
C
)
f
o
r
th
e
te
s
t d
ata.
T
ab
le
4
.
C
o
r
r
elatio
n
co
ef
f
icien
t b
etwe
en
th
e
p
r
ed
icted
a
n
d
e
x
p
er
im
en
tal
d
is
ch
ar
g
e
cu
r
r
en
t
s
R
e
f
e
r
e
n
c
e
P
C
C
G
a
r
a
mo
o
n
_
1
[
16
]
0
.
9
66
G
a
r
a
mo
o
n
_
2
[
1
6]
0
.
9
6
9
O
sawa
[
8]
0
.
9
6
5
R
a
n
[
11]
0
.
9
1
2
B
r
a
n
d
e
n
b
u
r
g
[
9
]
0
.
7
4
6
Ty
a
t
a
[
7
]
0.
7
8
6
B
e
d
o
u
i
[
18]
0.
8
9
6
T
h
e
r
an
d
o
m
f
o
r
est
r
e
g
r
ess
io
n
r
esu
lts
d
em
o
n
s
tr
ate
p
r
o
m
is
i
n
g
co
r
r
elatio
n
s
b
etwe
en
p
r
e
d
icted
an
d
ex
p
er
im
en
tal
d
is
ch
ar
g
e
c
u
r
r
e
n
t
wav
ef
o
r
m
s
ac
r
o
s
s
v
ar
io
u
s
r
ef
er
en
ce
s
tu
d
ies,
alb
eit
wit
h
s
o
m
e
v
ar
iatio
n
s
.
W
h
ile
h
ig
h
Pear
s
o
n
co
r
r
elatio
n
co
ef
f
icien
ts
(
PC
C
)
ex
ce
ed
in
g
0
.
9
in
s
ev
er
al
ca
s
es
in
d
icate
s
u
b
s
t
an
tial
p
r
ed
ictiv
e
ca
p
ab
ilit
y
,
in
c
o
n
s
is
ten
cies
s
u
g
g
est
ar
ea
s
f
o
r
f
u
r
th
er
im
p
r
o
v
em
en
t.
Fu
tu
r
e
en
h
an
ce
m
e
n
ts
m
ay
in
v
o
lv
e
e
x
p
an
d
in
g
th
e
d
ataset
to
in
clu
d
e
ad
d
itio
n
al
d
is
ch
ar
g
e
ex
p
e
r
im
en
ts
an
d
ex
p
l
o
r
in
g
a
wid
er
r
an
g
e
o
f
f
ea
tu
r
es
.
5.
DIS
CU
SS
I
O
N
T
h
is
s
tu
d
y
d
em
o
n
s
tr
ates
th
at
m
ac
h
in
e
lear
n
in
g
tech
n
iq
u
es,
s
p
ec
if
ically
r
an
d
o
m
f
o
r
est
class
if
icatio
n
an
d
r
eg
r
ess
io
n
,
e
f
f
ec
tiv
ely
cl
ass
if
y
Ho
m
o
g
en
e
o
u
s
a
n
d
Fil
am
en
tar
y
d
is
ch
ar
g
e
m
o
d
es
in
DB
D
s
y
s
tem
s
an
d
p
r
ed
ict
Ho
m
o
g
en
e
o
u
s
d
is
ch
a
r
g
e
cu
r
r
en
ts
.
Ach
iev
in
g
8
0
%
class
if
icatio
n
ac
cu
r
a
cy
,
th
e
m
o
d
el
p
er
f
o
r
m
ed
s
tr
o
n
g
ly
u
s
in
g
f
ea
tu
r
es
lik
e
a
p
p
lied
v
o
ltag
e,
g
as
g
ap
,
an
d
d
ielec
tr
ic
m
ater
ial.
T
h
e
h
ig
h
co
r
r
elatio
n
b
etwe
en
p
r
ed
icted
a
n
d
e
x
p
er
im
e
n
tal
wav
ef
o
r
m
s
in
r
eg
r
ess
io
n
f
u
r
t
h
er
s
u
p
p
o
r
ts
its
ab
ilit
y
to
p
r
ed
ict
Ho
m
o
g
e
n
eo
u
s
cu
r
r
en
t
wa
v
ef
o
r
m
s
.
T
h
ese
r
esu
lts
h
ig
h
lig
h
t
th
e
p
o
ten
tial
o
f
ML
-
d
r
iv
e
n
ap
p
r
o
ac
h
es
i
n
m
o
d
ellin
g
DB
D
s
y
s
tem
s
,
wh
ich
tr
ad
itio
n
ally
r
ely
o
n
co
m
p
lex
p
h
y
s
ical
m
o
d
els.
T
h
e
co
n
f
u
s
io
n
m
atr
ix
o
f
f
e
r
s
v
alu
ab
le
in
s
ig
h
ts
in
to
th
e
m
o
d
el
’
s
p
er
f
o
r
m
an
ce
an
d
ar
ea
s
f
o
r
im
p
r
o
v
em
e
n
t.
C
o
m
p
ar
ed
to
p
r
e
v
io
u
s
s
tu
d
ies,
th
is
wo
r
k
u
n
d
er
s
co
r
es
th
e
ad
v
an
tag
es
o
f
m
ac
h
in
e
lear
n
in
g
in
p
lasma
s
y
s
tem
m
o
d
ellin
g
.
Un
lik
e
r
e
s
ea
r
ch
r
ely
in
g
h
ea
v
ily
o
n
n
u
m
er
ical
s
im
u
latio
n
s
,
th
is
s
tu
d
y
u
s
es
d
ata
-
d
r
iv
e
n
m
eth
o
d
s
,
o
f
f
e
r
in
g
g
r
ea
ter
f
lex
i
b
ilit
y
an
d
ef
f
icien
cy
in
a
d
d
r
es
s
in
g
n
o
n
lin
ea
r
r
elatio
n
s
h
ip
s
b
etwe
en
f
ea
tu
r
es a
n
d
d
is
ch
ar
g
e
b
e
h
av
io
u
r
s
.
Ho
wev
er
,
m
is
class
if
icatio
n
s
,
p
ar
ticu
lar
ly
f
alse
p
o
s
itiv
es
wh
er
e
Fil
am
en
tar
y
d
is
ch
ar
g
e
s
wer
e
p
r
ed
icted
as
Ho
m
o
g
en
e
o
u
s
,
r
em
ain
a
lim
itatio
n
.
T
h
is
co
u
ld
s
tem
f
r
o
m
f
ea
tu
r
e
o
v
e
r
lap
o
r
in
s
u
f
f
icien
t
d
ata
to
f
u
lly
ca
p
tu
r
e
t
h
e
d
if
f
e
r
en
ce
s
b
etwe
en
m
o
d
es.
T
h
e
s
tu
d
y
’
s
p
r
im
ar
y
aim
was
to
ex
p
lo
r
e
m
ac
h
in
e
lear
n
in
g
ap
p
licatio
n
s
in
class
if
y
in
g
d
is
ch
ar
g
e
m
o
d
es
an
d
p
r
e
d
ictin
g
d
is
ch
ar
g
e
cu
r
r
e
n
ts
in
DB
D
s
y
s
tem
s
.
I
t
b
r
id
g
es
th
e
g
ap
b
etwe
en
p
h
y
s
ical
m
o
d
ellin
g
an
d
da
ta
-
d
r
iv
e
n
ap
p
r
o
ac
h
es,
p
r
o
v
id
in
g
in
s
ig
h
ts
in
to
n
o
n
-
t
h
er
m
al
p
lasma
s
y
s
tem
s
.
Ho
wev
er
,
q
u
esti
o
n
s
r
em
ain
,
s
u
ch
as
wh
eth
er
a
m
o
r
e
d
iv
er
s
e
d
ataset
co
u
ld
im
p
r
o
v
e
p
er
f
o
r
m
an
ce
.
Fu
tu
r
e
r
esear
ch
s
h
o
u
l
d
f
o
cu
s
o
n
r
e
f
in
in
g
f
ea
tu
r
e
s
elec
tio
n
,
ex
p
a
n
d
in
g
d
atasets
,
an
d
en
h
an
cin
g
m
o
d
el
s
en
s
itiv
ity
to
r
ed
u
ce
m
is
c
lass
if
icatio
n
s
an
d
im
p
r
o
v
e
p
r
ed
ictiv
e
ac
c
u
r
ac
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
39
,
No
.
1
,
J
u
ly
20
25
:
101
-
1
0
9
108
6.
CO
NCLU
SI
O
N
I
n
th
is
s
tu
d
y
,
we
p
r
esen
ted
a
co
m
p
r
eh
e
n
s
iv
e
ap
p
r
o
ac
h
to
m
o
d
ellin
g
d
is
ch
ar
g
e
cu
r
r
en
t
s
in
DB
D
s
y
s
tem
s
u
s
in
g
m
ac
h
in
e
lear
n
in
g
tec
h
n
iq
u
es,
s
p
ec
if
ically
r
an
d
o
m
f
o
r
est
class
if
icatio
n
an
d
r
e
g
r
ess
io
n
alg
o
r
ith
m
s
.
W
e
s
u
cc
ess
f
u
lly
class
if
ied
Ho
m
o
g
e
n
eo
u
s
a
n
d
Fil
am
en
ta
r
y
d
is
ch
ar
g
e
m
o
d
es
an
d
p
r
ed
icte
d
Ho
m
o
g
en
e
o
u
s
d
is
ch
ar
g
e
cu
r
r
en
ts
with
h
ig
h
ac
cu
r
ac
y
in
class
if
icatio
n
an
d
s
tr
o
n
g
co
r
r
elatio
n
s
b
etwe
en
p
r
ed
icted
a
n
d
ex
p
e
r
im
en
tal
wav
ef
o
r
m
s
in
r
eg
r
ess
io
n
.
T
h
ese
f
in
d
in
g
s
c
o
n
tr
ib
u
te
v
al
u
a
b
le
in
s
ig
h
ts
to
c
o
ld
p
lasma
r
esear
ch
,
s
h
o
win
g
th
a
t
ML
m
eth
o
d
s
ca
n
en
h
a
n
ce
o
u
r
ab
ilit
y
to
m
o
d
el
a
n
d
p
r
e
d
ict
DB
D
b
eh
av
io
u
r
s
,
wh
ich
h
av
e
tr
ad
itio
n
ally
r
elied
o
n
p
h
y
s
ical
m
o
d
els.
T
h
e
class
if
icatio
n
m
o
d
el
also
s
er
v
es
as a
v
alu
ab
le
to
o
l f
o
r
u
n
d
er
s
tan
d
i
n
g
th
e
im
p
ac
t
o
f
ex
p
e
r
im
en
tal
f
ea
tu
r
es
o
n
d
is
ch
ar
g
e
m
o
d
es.
H
o
wev
e
r
,
d
is
cr
ep
an
cies
in
class
if
icatio
n
an
d
r
eg
r
ess
io
n
p
er
f
o
r
m
an
ce
s
u
g
g
est
th
e
n
ee
d
f
o
r
f
u
r
th
er
in
v
esti
g
atio
n
in
t
o
f
ea
tu
r
e
s
elec
tio
n
,
m
o
d
el
r
ef
i
n
em
en
t,
a
n
d
d
ataset
ex
p
an
s
io
n
t
o
im
p
r
o
v
e
ac
c
u
r
a
cy
an
d
r
o
b
u
s
tn
ess
.
T
h
is
ca
n
lead
to
b
etter
c
o
n
tr
o
l
o
f
p
lasma
p
r
o
ce
s
s
es
in
in
d
u
s
tr
ial,
m
ed
ical,
an
d
e
n
v
ir
o
n
m
e
n
tal
ap
p
licatio
n
s
.
Ov
er
all,
o
u
r
f
in
d
in
g
s
h
i
g
h
lig
h
t
th
e
p
o
ten
tial
o
f
d
ata
-
d
r
iv
en
m
o
d
ellin
g
to
ad
v
a
n
ce
o
u
r
u
n
d
er
s
tan
d
in
g
o
f
DB
D
s
y
s
tem
s
an
d
en
h
an
ce
p
r
e
d
ictiv
e
ca
p
ab
ilit
ies,
with
f
u
tu
r
e
r
esear
ch
f
o
cu
s
in
g
o
n
r
ef
in
in
g
m
o
d
el
s
an
d
m
eth
o
d
o
lo
g
ies f
o
r
ev
e
n
g
r
ea
ter
p
r
ec
is
io
n
.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
N
o
f
u
n
d
in
g
in
v
o
lv
e
d
.
AUTHO
R
CO
NT
RI
B
UT
I
O
NS ST
A
T
E
M
E
N
T
Na
m
e
o
f
Aut
ho
r
C
M
So
Va
Fo
I
R
D
O
E
Vi
Su
P
Fu
L
aiad
i A
b
d
elh
am
id
✓
✓
✓
✓
✓
✓
✓
✓
✓
C
h
en
to
u
f
Ab
d
ella
h
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
E
zz
iy
an
i M
u
s
tap
h
a
✓
✓
✓
✓
✓
✓
C
:
C
o
n
c
e
p
t
u
a
l
i
z
a
t
i
o
n
M
:
M
e
t
h
o
d
o
l
o
g
y
So
:
So
f
t
w
a
r
e
Va
:
Va
l
i
d
a
t
i
o
n
Fo
:
Fo
r
mal
a
n
a
l
y
s
i
s
I
:
I
n
v
e
s
t
i
g
a
t
i
o
n
R
:
R
e
so
u
r
c
e
s
D
:
D
a
t
a
C
u
r
a
t
i
o
n
O
:
W
r
i
t
i
n
g
-
O
r
i
g
i
n
a
l
D
r
a
f
t
E
:
W
r
i
t
i
n
g
-
R
e
v
i
e
w
&
E
d
i
t
i
n
g
Vi
:
Vi
su
a
l
i
z
a
t
i
o
n
Su
:
Su
p
e
r
v
i
s
i
o
n
P
:
P
r
o
j
e
c
t
a
d
mi
n
i
st
r
a
t
i
o
n
Fu
:
Fu
n
d
i
n
g
a
c
q
u
i
si
t
i
o
n
CO
NF
L
I
C
T
O
F
I
N
T
E
R
E
S
T
ST
A
T
E
M
E
NT
Au
th
o
r
s
s
tate
n
o
co
n
f
lict o
f
in
t
er
est.
DATA AV
AI
L
AB
I
L
I
T
Y
Der
iv
ed
d
ata
s
u
p
p
o
r
ti
n
g
th
e
f
in
d
in
g
s
o
f
th
is
s
tu
d
y
ar
e
av
ailab
le
f
r
o
m
th
e
co
r
r
esp
o
n
d
i
n
g
au
th
o
r
(
L.
Ab
d
elh
a
m
id
)
o
n
r
e
q
u
est.
RE
F
E
R
E
NC
E
S
[
1
]
R
.
B
r
a
n
d
e
n
b
u
r
g
,
K
.
H
.
B
e
c
k
e
r
a
n
d
K
.
-
D
.
W
e
l
t
ma
n
n
,
“
B
a
r
r
i
e
r
d
i
sc
h
a
r
g
e
s
i
n
s
c
i
e
n
c
e
a
n
d
t
e
c
h
n
o
l
o
g
y
s
i
n
c
e
2
0
0
3
:
A
t
r
i
b
u
t
e
a
n
d
u
p
d
a
t
e
,”
Pl
a
sm
a
C
h
e
m
i
st
r
y
a
n
d
Pl
a
s
m
a
Pr
o
c
e
ssi
n
g
,
A
u
g
.
2
0
2
3
,
d
o
i
:
1
0
.
1
0
0
7
/
s
1
1
0
9
0
-
0
2
3
-
1
0
3
6
4
-
5.
[
2
]
A
.
P
a
mr
e
d
d
y
e
t
a
l
.
,
“
P
l
a
sma
c
l
e
a
n
i
n
g
a
n
d
a
c
t
i
v
a
t
i
o
n
o
f
s
i
l
i
c
o
n
s
u
r
f
a
c
e
i
n
d
i
e
l
e
c
t
r
i
c
c
o
p
l
a
n
a
r
su
r
f
a
c
e
b
a
r
r
i
e
r
d
i
sch
a
r
g
e
,
”
S
u
r
f
a
c
e
a
n
d
C
o
a
t
i
n
g
s Te
c
h
n
o
l
o
g
y
,
v
o
l
.
2
3
6
,
p
p
.
3
2
6
–
3
3
1
,
D
e
c
.
2
0
1
3
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
su
r
f
c
o
a
t
.
2
0
1
3
.
1
0
.
0
0
8
.
[
3
]
S
.
U
.
K
a
l
g
h
a
t
g
i
,
G
.
F
r
i
d
ma
n
,
A
.
F
r
i
d
m
a
n
,
G
.
F
r
i
e
d
ma
n
a
n
d
A
.
M
.
C
l
y
n
e
,
“
N
o
n
-
t
h
e
r
ma
l
d
i
e
l
e
c
t
r
i
c
b
a
r
r
i
e
r
d
i
s
c
h
a
r
g
e
p
l
a
sma
t
r
e
a
t
me
n
t
o
f
e
n
d
o
t
h
e
l
i
a
l
c
e
l
l
s
,
”
2
0
0
8
3
0
t
h
A
n
n
u
a
l
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
f
t
h
e
I
EEE
En
g
i
n
e
e
r
i
n
g
i
n
M
e
d
i
c
i
n
e
a
n
d
Bi
o
l
o
g
y
S
o
c
i
e
t
y
,
V
a
n
c
o
u
v
e
r
,
B
C
,
C
a
n
a
d
a
,
,
v
o
l
.
2
0
0
8
,
p
p
.
3
5
7
8
–
3
5
8
1
,
2
0
0
8
,
d
o
i
:
1
0
.
1
1
0
9
/
I
EM
B
S
.
2
0
0
8
.
4
6
4
9
9
7
9
.
[
4
]
D
.
M
e
i
a
n
d
X
.
Tu
,
“
C
o
n
v
e
r
s
i
o
n
o
f
C
O
2
i
n
a
c
y
l
i
n
d
r
i
c
a
l
d
i
e
l
e
c
t
r
i
c
b
a
r
r
i
e
r
d
i
sc
h
a
r
g
e
r
e
a
c
t
o
r
:
Ef
f
e
c
t
s
o
f
p
l
a
sma
p
r
o
c
e
ss
i
n
g
p
a
r
a
m
e
t
e
r
s a
n
d
r
e
a
c
t
o
r
d
e
s
i
g
n
,
”
J
o
u
r
n
a
l
o
f
C
O
2
U
t
i
l
i
z
a
t
i
o
n
,
v
o
l
.
1
9
,
p
p
.
6
8
–
7
8
,
M
a
y
2
0
1
7
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
j
c
o
u
.
2
0
1
7
.
0
2
.
0
1
5
.
[
5
]
H
.
L
u
o
,
Z.
Li
a
n
g
,
B
.
L
v
,
X
.
W
a
n
g
,
Z
.
G
u
a
n
a
n
d
L.
W
a
n
g
,
“
O
b
ser
v
a
t
i
o
n
o
f
t
h
e
t
r
a
n
s
i
t
i
o
n
f
r
o
m
a
T
o
w
n
s
e
n
d
d
i
s
c
h
a
r
g
e
t
o
a
g
l
o
w
d
i
s
c
h
a
r
g
e
i
n
h
e
l
i
u
m
a
t
a
t
mo
sp
h
e
r
i
c
p
r
e
ssu
r
e
,
”
A
p
p
l
i
e
d
P
h
y
s
i
c
s
.
L
e
t
t
er
,
v
o
l
.
9
1
,
n
o
.
2
2
,
p
.
2
2
1
5
0
4
,
N
o
v
.
2
0
0
7
,
d
o
i
:
1
0
.
1
0
6
3
/
1
.
2
8
1
9
0
7
3
.
[
6
]
F
.
M
a
ssi
n
e
s,
N
.
G
h
e
r
a
r
d
i
,
N
.
N
a
u
d
é
a
n
d
P
.
S
é
g
u
r
,
“
G
l
o
w
a
n
d
To
w
n
se
n
d
d
i
e
l
e
c
t
r
i
c
b
a
r
r
i
e
r
d
i
s
c
h
a
r
g
e
i
n
v
a
r
i
o
u
s
a
t
mo
sp
h
e
r
e
,
”
Pl
a
sm
a
Ph
y
si
c
s
a
n
d
C
o
n
t
ro
l
l
e
d
F
u
si
o
n
,
v
o
l
.
4
7
,
n
o
.
1
2
B
,
p
.
B
5
7
7
,
N
o
v
.
2
0
0
5
,
d
o
i
:
1
0
.
1
0
8
8
/
0
7
4
1
-
3
3
3
5
/
4
7
/
1
2
B
/
S
4
2
.
[
7
]
R
.
S
h
r
e
st
h
a
,
R
.
B
.
T
y
a
t
a
a
n
d
D
.
P
.
S
u
b
e
d
i
,
“
Ef
f
e
c
t
o
f
a
p
p
l
i
e
d
v
o
l
t
a
g
e
i
n
e
l
e
c
t
r
o
n
d
e
n
s
i
t
y
o
f
h
o
mo
g
e
n
e
o
u
s
d
i
e
l
e
c
t
r
i
c
b
a
r
r
i
e
r
d
i
s
c
h
a
r
g
e
a
t
a
t
m
o
sp
h
e
r
i
c
e
p
r
e
ss
u
r
e
,
”
H
i
m
a
l
a
y
a
Ph
y
s
i
c
s
.
,
v
o
l
.
4
,
p
p
.
1
0
–
1
3
,
D
e
c
.
2
0
1
3
,
d
o
i
:
1
0
.
3
1
2
6
/
h
j
.
v
4
i
0
.
9
4
1
8
.
[
8
]
N
.
O
sawa
a
n
d
Y
.
Y
o
sh
i
o
k
a
,
“
G
e
n
e
r
a
t
i
o
n
o
f
l
o
w
-
f
r
e
q
u
e
n
c
y
h
o
m
o
g
e
n
e
o
u
s
d
i
e
l
e
c
t
r
i
c
b
a
r
r
i
e
r
d
i
sc
h
a
r
g
e
a
t
a
t
m
o
s
p
h
e
r
i
c
p
r
e
ss
u
r
e
,
”
I
EEE
T
r
a
n
s
a
c
t
i
o
n
s
o
n
Pl
a
sm
a
S
c
i
e
n
c
e
,
v
o
l
.
4
0
,
n
o
.
1
,
p
p
.
2
–
8
,
Ja
n
.
2
0
1
2
,
d
o
i
:
1
0
.
1
1
0
9
/
TPS
.
2
0
1
1
.
2
1
7
2
6
3
4
.
[
9
]
R
.
B
r
a
n
d
e
n
b
u
r
g
,
Z
.
N
a
v
r
á
t
i
l
,
J.
J
á
n
s
k
ý
,
P
.
S
t
’
a
h
e
l
,
D
.
Tr
u
n
e
c
a
n
d
H
.
-
E.
W
a
g
n
e
r
,
“
T
h
e
t
r
a
n
s
i
t
i
o
n
b
e
t
w
e
e
n
d
i
f
f
e
r
e
n
t
m
o
d
e
s
o
f
b
a
r
r
i
e
r
d
i
s
c
h
a
r
g
e
s
a
t
a
t
mo
sp
h
e
r
i
c
p
r
e
ssu
r
e
,
”
J
o
u
r
n
a
l
o
f
Ph
y
si
c
s
D
:
A
p
p
l
i
e
d
Ph
y
si
c
s
,
v
o
l
.
4
2
,
n
o
.
8
,
p
.
0
8
5
2
0
8
,
A
p
r
.
2
0
0
9
,
d
o
i
:
1
0
.
1
0
8
8
/
0
0
2
2
-
3
7
2
7
/
4
2
/
8
/
0
8
5
2
0
8
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
R
a
n
d
o
m
fo
r
est me
th
o
d
fo
r
p
r
ed
ictin
g
d
is
ch
a
r
g
e
c
u
r
r
en
t wa
ve
fo
r
m
a
n
d
mo
d
e
…
(
La
ia
d
i A
b
d
elh
a
mid
)
109
[
1
0
]
F
.
M
a
ss
i
n
e
s,
N
.
G
h
e
r
a
r
d
i
,
N
.
N
a
u
d
é
a
n
d
P
.
S
é
g
u
r
,
“
R
e
c
e
n
t
a
d
v
a
n
c
e
s
i
n
t
h
e
u
n
d
e
r
s
t
a
n
d
i
n
g
o
f
h
o
m
o
g
e
n
e
o
u
s
d
i
e
l
e
c
t
r
i
c
b
a
r
r
i
e
r
d
i
s
c
h
a
r
g
e
s,”
E
u
r.
Ph
y
s.
J
.
-
A
p
p
l
.
Ph
y
s.
,
v
o
l
.
4
7
,
n
o
.
2
,
p
.
2
2
8
0
5
,
A
u
g
.
2
0
0
9
,
d
o
i
:
1
0
.
1
0
5
1
/
e
p
j
a
p
/
2
0
0
9
0
6
4
.
[
1
1
]
J.
R
a
n
,
C
.
L
i
,
D
.
M
a
,
H
.
Lu
o
,
a
n
d
X
.
Li
,
“
H
o
m
o
g
e
n
e
o
u
s
d
i
e
l
e
c
t
r
i
c
b
a
r
r
i
e
r
d
i
sc
h
a
r
g
e
s
i
n
a
t
mo
s
p
h
e
r
i
c
a
i
r
a
n
d
i
t
s
i
n
f
l
u
e
n
c
i
n
g
f
a
c
t
o
r
,
”
Ph
y
s
i
c
s
Pl
a
sm
a
s
,
v
o
l
.
2
5
,
p
.
0
3
3
5
1
1
,
M
a
r
.
2
0
1
8
,
d
o
i
:
1
0
.
1
0
6
3
/
1
.
5
0
1
9
9
8
9
.
[
1
2
]
R
.
A
n
i
r
u
d
h
e
t
a
l
.
,
“
2
0
2
2
r
e
v
i
e
w
o
f
d
a
t
a
-
d
r
i
v
e
n
p
l
a
sma
sc
i
e
n
c
e
,
”
I
EEE
T
r
a
n
sa
c
t
i
o
n
s
o
n
P
l
a
sm
a
S
c
i
e
n
c
e
,
,
v
o
l
.
5
1
,
n
o
.
7
,
p
p
.
1
7
5
0
–
1
8
3
8
,
J
u
l
.
2
0
2
3
,
d
o
i
:
1
0
.
1
1
0
9
/
T
P
S
.
2
0
2
3
.
3
2
6
8
1
7
0
.
[
1
3
]
T.
G
uo
,
X
.
L
iu
,
S
.
H
ao
,
X
.
G
u
a
n
d
X
.
H
e
,
“
P
r
e
d
i
c
t
i
o
n
o
f
e
q
u
i
v
a
l
e
n
t
e
l
e
c
t
r
i
c
a
l
p
a
r
a
me
t
e
r
s o
f
d
i
e
l
e
c
t
r
i
c
b
a
r
r
i
e
r
d
i
sc
h
a
r
g
e
l
o
a
d
u
si
n
g
a
n
e
u
r
a
l
n
e
t
w
o
r
k
,
”
P
l
a
sm
a
S
c
i
e
n
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
1
7
,
n
o
.
3
,
p
.
1
9
6
,
M
a
r
.
2
0
1
5
,
d
o
i
:
1
0
.
1
0
8
8
/
1
0
0
9
-
0
6
3
0
/
1
7
/
3
/
0
5
.
[
1
4
]
J.
Tr
i
e
sc
h
m
a
n
n
,
L.
V
i
a
l
e
t
t
o
a
n
d
T.
G
e
r
g
s,
“
M
a
c
h
i
n
e
l
e
a
r
n
i
n
g
f
o
r
a
d
v
a
n
c
i
n
g
l
o
w
-
t
e
m
p
e
r
a
t
u
r
e
p
l
a
sma
m
o
d
e
l
i
n
g
a
n
d
s
i
m
u
l
a
t
i
o
n
.
”
a
rXi
v
,
Ju
n
.
3
0
,
2
0
2
3
.
d
o
i
:
1
0
.
4
8
5
5
0
/
a
r
X
i
v
.
2
3
0
7
.
0
0
1
3
1
.
[
1
5
]
S
.
Li
u
a
n
d
M
.
N
e
i
g
e
r
,
“
El
e
c
t
r
i
c
a
l
mo
d
e
l
l
i
n
g
o
f
h
o
mo
g
e
n
e
o
u
s
d
i
e
l
e
c
t
r
i
c
b
a
r
r
i
e
r
d
i
sc
h
a
r
g
e
s
u
n
d
e
r
a
n
a
r
b
i
t
r
a
r
y
e
x
c
i
t
a
t
i
o
n
v
o
l
t
a
g
e
,
”
J
o
u
rn
a
l
o
f
Ph
y
si
c
s D:
A
p
p
l
i
e
d
P
h
y
s
i
c
s
,
v
o
l
.
3
6
,
n
o
.
2
4
,
p
.
3
1
4
4
,
N
o
v
.
2
0
0
3
,
d
o
i
:
1
0
.
1
0
8
8
/
0
0
2
2
-
3
7
2
7
/
3
6
/
2
4
/
0
0
9
.
[
1
6
]
A
.
A
.
G
a
r
a
m
o
o
n
a
n
d
D
.
M
.
E
l
-
z
e
e
r
,
“
A
t
m
o
sp
h
e
r
i
c
p
r
e
ss
u
r
e
g
l
o
w
d
i
s
c
h
a
r
g
e
p
l
a
sm
a
i
n
a
i
r
a
t
f
r
e
q
u
e
n
c
y
5
0
H
z
,
”
Pl
a
sm
a
S
o
u
r
c
e
s
S
c
i
e
n
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
1
8
,
n
o
.
4
,
p
.
0
4
5
0
0
6
,
N
o
v
.
2
0
0
9
,
d
o
i
:
1
0
.
1
0
8
8
/
0
9
6
3
-
0
2
5
2
/
1
8
/
4
/
0
4
5
0
0
6
.
[
1
7
]
S
.
B
h
o
sl
e
e
t
a
l
.
,
“
El
e
c
t
r
i
c
a
l
m
o
d
e
l
i
n
g
o
f
a
n
h
o
m
o
g
e
n
e
o
u
s
d
i
e
l
e
c
t
r
i
c
b
a
r
r
i
e
r
d
i
sc
h
a
r
g
e
(
D
B
D
)
,
”
i
n
F
o
u
r
t
i
e
t
h
I
AS
An
n
u
a
l
M
e
e
t
i
n
g
.
C
o
n
f
e
re
n
c
e
R
e
c
o
rd
o
f
t
h
e
2
0
0
5
I
n
d
u
st
r
y
A
p
p
l
i
c
a
t
i
o
n
s
C
o
n
f
e
re
n
c
e
,
2
0
0
5
.
,
O
c
t
.
2
0
0
5
,
p
p
.
2
3
1
5
-
2
3
1
9
V
o
l
.
4
.
d
o
i
:
1
0
.
1
1
0
9
/
I
A
S
.
2
0
0
5
.
1
5
1
8
7
8
3
.
[
1
8
]
M
.
B
e
d
o
u
i
,
A
.
W
.
B
e
l
a
r
b
i
,
a
n
d
S
.
H
a
b
i
b
e
s
,
“
M
a
c
r
o
sc
o
p
i
c
mo
d
e
l
i
n
g
o
f
t
h
e
g
l
o
w
d
i
e
l
e
c
t
r
i
c
b
a
r
r
i
e
r
d
i
sc
h
a
r
g
e
(
G
D
B
D
)
i
n
h
e
l
i
u
m,
”
Eu
r
o
p
e
a
n
J
o
u
r
n
a
l
o
f
E
l
e
c
t
ri
c
a
l
En
g
i
n
e
e
ri
n
g
,
v
o
l
.
2
0
,
n
o
.
1
,
p
p
.
8
9
–
1
0
3
,
F
e
b
.
2
0
1
8
,
d
o
i
:
1
0
.
3
1
6
6
/
e
j
e
e
.
2
0
.
8
9
-
1
0
3
.
[
1
9
]
L.
M
a
n
g
o
l
i
n
i
,
C
.
A
n
d
e
r
so
n
,
J
.
H
e
b
e
r
l
e
i
n
,
a
n
d
U
.
K
o
r
t
sh
a
g
e
n
,
“
Ef
f
e
c
t
s
o
f
c
u
r
r
e
n
t
l
i
m
i
t
a
t
i
o
n
t
h
r
o
u
g
h
t
h
e
d
i
e
l
e
c
t
r
i
c
i
n
a
t
m
o
s
p
h
e
r
i
c
p
r
e
ss
u
r
e
g
l
o
w
s
i
n
h
e
l
i
u
m,
”
J
o
u
r
n
a
l
o
f
Ph
y
si
c
s
D
:
Ap
p
l
i
e
d
P
h
y
si
c
s
,
v
o
l
.
3
7
,
n
o
.
7
,
p
.
1
0
2
1
,
M
a
r
.
2
0
0
4
,
d
o
i
:
1
0
.
1
0
8
8
/
0
0
2
2
-
3
7
2
7
/
3
7
/
7
/
0
1
2
.
[
2
0
]
D
.
M
.
E
l
-
Ze
e
r
,
A
.
S
a
mi
r
,
F
.
El
a
k
s
h
a
r
,
a
n
d
A
.
A
.
G
a
r
a
mo
o
n
,
“
D
e
c
a
y
i
n
g
o
f
n
i
t
r
o
g
e
n
se
c
o
n
d
p
o
si
t
i
v
e
sy
s
t
e
m
b
y
a
d
d
i
t
i
o
n
o
f
H
2
g
a
s
i
n
a
i
r
D
B
d
i
s
c
h
a
r
g
e
,
”
J
o
u
rn
a
l
o
f
Mo
d
e
rn
Ph
y
si
c
s
,
v
o
l
.
4
,
n
o
.
2
,
A
r
t
.
n
o
.
2
,
F
e
b
.
2
0
1
3
,
d
o
i
:
1
0
.
4
2
3
6
/
j
m
p
.
2
0
1
3
.
4
2
0
2
2
.
[
2
1
]
D
.
Tr
u
n
e
c
,
A
.
B
r
a
b
l
e
c
a
n
d
J.
B
u
c
h
t
a
,
“
A
t
m
o
sp
h
e
r
i
c
p
r
e
ss
u
r
e
g
l
o
w
d
i
sc
h
a
r
g
e
i
n
n
e
o
n
,
”
J
o
u
rn
a
l
o
f
P
h
y
s
i
c
s D:
A
p
p
l
i
e
d
P
h
y
s
i
c
s
,
v
o
l
.
3
4
,
n
o
.
1
1
,
p
.
1
6
9
7
,
Ju
n
.
2
0
0
1
,
d
o
i
:
1
0
.
1
0
8
8
/
0
0
2
2
-
3
7
2
7
/
3
4
/
1
1
/
3
2
2
.
[
2
2
]
E.
A
l
p
a
y
d
i
n
,
I
n
t
r
o
d
u
c
t
i
o
n
t
o
M
a
c
h
i
n
e
L
e
a
r
n
i
n
g
.
M
I
T
P
r
e
ss,
2
0
1
0
.
[
2
3
]
Z.
-
H
.
Z
h
o
u
,
E
n
sem
b
l
e
M
e
t
h
o
d
s:
Fo
u
n
d
a
t
i
o
n
s
a
n
d
Al
g
o
r
i
t
h
m
s
.
C
R
C
P
r
e
ss,
2
0
1
2
.
[
2
4
]
A
.
S
a
r
i
d
j
a
n
d
A
.
W
.
B
e
l
a
r
b
i
,
“
N
u
mer
i
c
a
l
m
o
d
e
l
i
n
g
o
f
a
D
B
D
i
n
g
l
o
w
m
o
d
e
a
t
a
t
mo
s
p
h
e
r
i
c
p
r
e
ss
u
r
e
,
”
J
o
u
rn
a
l
o
f
T
h
e
o
r
e
t
i
c
a
l
a
n
d
Ap
p
l
i
e
d
P
h
y
s
i
c
s
,
v
o
l
.
1
3
,
n
o
.
3
,
p
p
.
1
7
9
–
1
9
0
,
S
e
p
.
2
0
1
9
,
d
o
i
:
1
0
.
1
0
0
7
/
s
4
0
0
9
4
-
0
1
9
-
0
0
3
4
0
-
w.
[
2
5
]
J.
A
.
L
ó
p
e
z
-
F
e
r
n
a
n
d
e
z
e
t
a
l
.
,
“
E
l
e
c
t
r
i
c
a
l
m
o
d
e
l
o
f
d
i
e
l
e
c
t
r
i
c
b
a
r
r
i
e
r
d
i
sc
h
a
r
g
e
h
o
m
o
g
e
n
o
u
s
a
n
d
f
i
l
a
m
e
n
t
a
r
y
m
o
d
e
s,
”
J
o
u
rn
a
l
o
f
Ph
y
s
i
c
s:
C
o
n
f
e
r
e
n
c
e
S
e
ri
e
s
,
v
o
l
.
7
9
2
,
p
.
0
1
2
0
6
7
,
Ja
n
.
2
0
1
7
,
d
o
i
:
1
0
.
1
0
8
8
/
1
7
4
2
-
6
5
9
6
/
7
9
2
/
1
/
0
1
2
0
6
7
.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
La
ia
d
i
Abd
e
lh
a
m
i
d
He
is a P
h
.
D.
s
tu
d
e
n
t
a
t
t
h
e
F
a
c
u
lt
y
o
f
S
c
ie
n
c
e
a
n
d
Tec
h
n
o
lo
g
ie
s
in
Tan
g
ier
.
H
e
wo
rk
s
o
n
t
h
e
su
b
jec
t
o
f
e
lec
tri
c
a
l
m
o
d
e
ll
in
g
o
f
c
o
ld
p
las
m
a
a
n
d
th
e
d
iele
c
tri
c
b
a
rrier
d
isc
h
a
rg
e
(DBD
).
H
e
o
b
tai
n
e
d
h
is
e
n
g
in
e
e
rin
g
d
e
g
re
e
in
e
lec
tro
n
ics
s
y
ste
m
s
a
n
d
a
u
to
m
a
ti
on
in
2
0
1
5
fro
m
t
h
e
N
a
ti
o
n
a
l
S
c
h
o
o
l
o
f
A
p
p
li
e
d
S
c
i
e
n
c
e
s
o
f
Tan
g
ier,
Ab
d
e
lma
lek
Essa
a
d
i
Un
iv
e
rsity
,
M
o
ro
c
c
o
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
a
.
laia
d
i
@u
a
e
.
a
c
.
m
a
.
Chento
u
f
Abd
e
ll
a
h
He
is
a
n
a
ss
o
c
iate
p
ro
fe
ss
o
r
a
t
F
a
c
u
lt
y
o
f
S
c
ien
c
e
s
a
n
d
Tec
h
n
o
l
o
g
ies
o
f
Tan
g
ier,
Ab
d
e
l
m
a
lek
Essa
a
d
i
Un
iv
e
rsity
,
M
o
r
o
c
c
o
,
He
h
o
l
d
s
a
P
h
.
D.
d
e
g
re
e
in
En
e
rg
y
a
n
d
P
ro
c
e
ss
E
n
g
i
n
e
e
rin
g
fro
m
Eco
le
Ce
n
tral
o
f
Na
n
tes
,
F
ra
n
c
e
.
His
re
se
a
rc
h
f
o
c
u
se
s
o
n
th
e
a
p
p
li
c
a
ti
o
n
s
o
f
c
o
m
p
u
t
in
g
a
n
d
n
u
m
e
rica
l
m
e
th
o
d
s
f
o
r
m
o
d
e
ll
i
n
g
e
lec
tri
c
a
n
d
e
lec
tro
m
a
g
n
e
ti
c
p
ro
b
lem
s
.
He
h
a
s
d
e
v
e
lo
p
e
d
a
p
a
c
k
a
g
e
fo
r
m
o
d
e
ll
i
n
g
a
RF
in
d
u
c
ti
o
n
p
las
m
a
in
sta
ll
a
ti
o
n
a
n
d
is
p
a
rti
c
u
larly
in
tere
ste
d
i
n
e
lec
tri
c
a
l
m
o
d
e
ll
in
g
o
f
c
o
ld
p
las
m
a
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
ac
h
e
n
to
u
f@
u
a
e
.
a
c
.
m
a
.
Zia
n
i
M
o
u
sta
p
h
a
He
r
e
c
e
iv
e
d
th
e
P
h
.
D.
d
e
g
re
e
in
I
n
fo
rm
a
ti
o
n
S
y
ste
m
En
g
in
e
e
rin
g
fro
m
M
o
h
a
m
m
e
d
V
Un
iv
e
rsity
i
n
1
9
9
9
,
Ra
b
a
t,
M
o
r
o
c
c
o
.
He
is
a
IEE
E
M
e
m
b
e
r,
His
re
se
a
rc
h
a
c
ti
v
it
ies
fo
c
u
s
o
n
a
d
v
a
n
c
i
n
g
d
a
ta
a
n
a
ly
sis,
p
ro
g
ra
m
m
in
g
,
a
n
d
m
a
c
h
in
e
lea
rn
in
g
,
c
o
n
tr
ib
u
ti
n
g
in
n
o
v
a
ti
v
e
m
o
d
e
ls
fo
r
d
e
c
isio
n
su
p
p
o
rt
in
v
a
ri
o
u
s
field
s.
He
d
e
sig
n
s
e
ffe
c
ti
v
e
sy
ste
m
s
fo
r
imp
lem
e
n
ti
n
g
d
e
c
isio
n
-
m
a
k
in
g
p
ro
c
e
ss
e
s,
e
m
p
o
we
rin
g
o
r
g
a
n
iza
ti
o
n
s
t
o
u
ti
li
z
e
d
a
ta
e
ffe
c
ti
v
e
ly
in
p
ra
c
ti
c
a
l
a
p
p
l
ica
ti
o
n
s.
He
is
c
u
rre
n
tl
y
a
p
ro
fe
ss
o
r
o
f
c
o
m
p
u
ter
En
g
i
n
e
e
rin
g
a
n
d
i
n
fo
rm
a
ti
o
n
S
y
ste
m
in
F
a
c
u
lt
y
o
f
S
c
ie
n
c
e
a
n
d
Tec
h
n
o
l
o
g
ies
,
Ab
d
e
lma
lek
Essa
a
d
i
Un
iv
e
rsit
y
,
M
o
r
o
c
c
o
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
m
e
z
z
iy
y
a
n
i@u
a
e
.
a
c
.
m
a
.
Evaluation Warning : The document was created with Spire.PDF for Python.