I
A
E
S
I
n
t
e
r
n
at
io
n
al
Jou
r
n
al
of
A
r
t
if
ic
ia
l
I
n
t
e
ll
ig
e
n
c
e
(
I
J
-
AI
)
V
ol
.
14
, N
o.
3
,
J
une
2025
, pp.
1790
~
1798
I
S
S
N
:
2252
-
8938
,
D
O
I
:
10.11591/
ij
a
i.
v
14
.i
3
.pp
1790
-
1798
1790
Jou
r
n
al
h
om
e
page
:
ht
tp
:
//
ij
ai
.
ia
e
s
c
or
e
.c
om
A
p
p
l
i
c
at
i
on
of
t
h
e
ad
ap
t
i
ve
n
e
u
r
o
-
f
u
z
z
y i
n
f
e
r
e
n
c
e
sys
t
e
m
f
or
p
r
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i
c
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on
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t
h
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l
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t
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gy p
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od
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c
t
i
on
i
n
J
a
k
ar
t
a
Y
oga
T
r
i
N
u
gr
ah
a
1
, C
at
r
a I
n
d
r
a C
ah
yad
i
2
, R
iz
k
h
a R
id
a
3
,
M
ar
gi
e
S
u
b
ah
agi
a N
in
gs
ih
3
, D
e
w
i
S
h
ol
e
h
a
4
,
I
n
d
r
a R
oz
a
5
1
D
e
pa
r
t
m
e
nt
of
E
l
e
c
t
r
i
c
a
l
E
ngi
ne
e
r
i
ng,
F
a
c
ul
t
y of
E
ngi
ne
e
r
i
ng,
U
ni
ve
r
s
i
t
a
s
A
l
-
A
z
ha
r
M
e
da
n
, M
e
da
n, I
ndone
s
i
a
2
D
e
pa
r
t
m
e
nt
of
E
l
e
c
t
r
i
c
a
l
A
i
r
por
t
E
ngi
ne
e
r
i
ng, P
ol
i
t
e
kni
k P
e
ne
r
ba
nga
n M
e
da
n,
M
e
da
n, I
ndone
s
i
a
3
D
e
pa
r
t
m
e
nt
of
I
ndus
t
r
i
a
l
E
ngi
ne
e
r
i
ng
, F
a
c
ul
t
y o
f
E
ngi
ne
e
r
i
ng,
U
ni
ve
r
s
i
t
a
s
A
l
-
A
z
ha
r
M
e
da
n
, M
e
da
n, I
ndone
s
i
a
4
D
e
pa
r
t
m
e
nt
of
E
l
e
c
t
r
i
c
a
l
E
ngi
ne
e
r
i
ng
,
F
a
c
ul
t
y of
E
ngi
ne
e
r
i
ng,
U
ni
ve
r
s
i
t
a
s
D
a
r
m
a
A
gung, M
e
da
n, I
ndone
s
i
a
5
D
e
pa
r
t
m
e
nt
of
E
l
e
c
t
r
i
c
a
l
E
ngi
ne
e
r
i
ng
,
F
a
c
ul
t
y of
E
ngi
ne
e
r
i
ng a
nd C
om
put
e
r
,
U
ni
ve
r
s
i
t
a
s
H
a
r
a
pa
n
M
e
da
n, M
e
da
n, I
ndone
s
i
a
A
r
t
ic
le
I
n
f
o
A
B
S
T
R
A
C
T
A
r
ti
c
le
h
is
to
r
y
:
R
e
c
e
iv
e
d
M
a
r
19, 2024
R
e
vi
s
e
d
J
a
n 28, 2025
A
c
c
e
pt
e
d
M
a
r
15, 2025
Jakarta,
as
a
rapidly
growing
urban
area,
faces
challenges
in
bal
ancing
energy
demand
with
supply
while
addressing
environmental
co
ncerns
associated
with
traditi
onal
energy
sources.
Electrical
energy
prod
uction
prediction
in
urban
environments
like
Jakarta
is
crucial
for
effective
energy
manageme
nt,
ensuring
stable
supply,
and
promoting
sust
ainable
development.
The
prediction
of
electrical
energy
production
in
Jak
arta
is
critical
for
ensuring
stable
and
sustain
able
energy
supply
.
This
re
search
proposed
the
applicati
on
of
the
adaptive
neuro
-
fuzzy
infer
ence
system
(
ANFIS
)
as
a
predictive
tool
specifically
tailored
for
Jakarta
'
s
energy
production
prediction
context.
The
research
methodology
used
in
this
study
is
the
ANFIS.
Five
levels
make
up
the
architecture
of
the
ANFIS
model:
output, normalization, defuzzification, rule e
valuation, and fuzzification. The
fuzzification
layer
converts
input
variables
into
linguis
tic
terms
using
membership
functions,
while
the
rule
evaluation
layer
calculat
es
the
activati
on
strength
of
each
rule
based
on
the
input
values.
The
pr
edicted
resul
ts
of
Jakarta
electrical
energy
production
from
2023
to
20
28
are
65
,
288
GWh
and
there
is
an
annual
increase
of
5.25%.
The
error
co
ntained
in
ANFIS
is
with
a
root
mean
square
error
(
RMSE
)
value
of
0.000
1058%
and a
mean abso
lute perc
entage e
rror
(
MAPE
)
value of 0.00875%.
K
e
y
w
o
r
d
s
:
A
N
F
I
S
A
ppl
ic
a
ti
on
E
le
c
tr
ic
a
l
e
ne
r
gy
J
a
ka
r
ta
P
r
e
di
c
ti
on
P
r
oduc
ti
on
This is an
open
acce
ss artic
le unde
r the
CC BY
-
SA
license.
C
or
r
e
s
pon
di
n
g A
u
th
or
:
Y
oga
T
r
i
N
ugr
a
ha
D
e
pa
r
tm
e
nt
of
E
le
c
tr
ic
a
l
E
ngi
ne
e
r
in
g, F
a
c
ul
ty
of
E
ngi
ne
e
r
in
g,
U
ni
ve
r
s
it
a
s
A
l
-
A
z
ha
r
M
e
d
a
n
P
in
tu
A
ir
I
V
R
oa
d N
o. 214, M
e
da
n 20142, Nor
th
S
um
a
tr
a
, I
ndone
s
ia
E
m
a
il
:
yoga
tr
in
ugr
a
ha
16
@
gm
a
il
.c
om
1.
I
N
T
R
O
D
U
C
T
I
O
N
A
n
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on
is
a
c
or
ne
r
s
to
ne
of
m
ode
r
n
c
iv
il
iz
a
ti
on,
pr
ovi
di
ng
th
e
e
s
s
e
nt
ia
l
pow
e
r
ne
e
de
d
f
or
hom
e
s
,
bus
in
e
s
s
e
s
,
in
dus
tr
ie
s
,
a
nd
t
e
c
hnol
o
gi
c
a
l
a
dva
nc
e
m
e
nt
s
[
1]
.
T
h
e
pr
oc
e
s
s
in
vol
ve
s
c
onve
r
ti
ng
va
r
io
us
pr
im
a
r
y
e
ne
r
gy
s
our
c
e
s
in
to
e
le
c
tr
ic
it
y,
w
h
ic
h
is
th
e
n
di
s
tr
ib
ut
e
d
th
r
ough
th
e
pow
e
r
gr
id
to
e
nd
-
us
e
r
s
.
U
nde
r
s
ta
ndi
ng
th
e
di
ve
r
s
e
m
e
th
ods
of
ge
ne
r
a
ti
ng
e
le
c
tr
ic
a
l
e
ne
r
gy,
th
e
ir
be
ne
f
it
s
,
a
nd
th
e
ir
e
nvi
r
onm
e
nt
a
l
im
pa
c
ts
is
c
r
uc
ia
l
f
or
de
ve
lo
pi
ng
s
us
ta
in
a
bl
e
e
n
e
r
gy
s
tr
a
te
gi
e
s
a
nd
a
ddr
e
s
s
in
g
th
e
c
ha
ll
e
nge
s
pos
e
d
by
c
li
m
a
te
c
ha
nge
[
2]
,
[
3]
.
A
s
th
e
gl
oba
l
e
le
c
tr
ic
it
y
de
m
a
nd
c
ont
in
ue
s
to
r
is
e
,
th
e
la
nds
c
a
pe
of
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on
is
und
e
r
goi
ng
a
tr
a
ns
f
or
m
a
ti
ve
s
hi
f
t.
T
hi
s
c
ha
nge
is
dr
iv
e
n
by
th
e
ne
e
d
f
or
s
us
ta
in
a
bl
e
a
nd
e
nvi
r
onm
e
nt
a
ll
y
f
r
ie
ndl
y
e
ne
r
gy
s
our
c
e
s
t
o
c
om
ba
t
c
li
m
a
te
c
ha
ng
e
a
nd
r
e
duc
e
our
de
pe
nde
nc
e
on
f
os
s
il
f
ue
ls
[
4]
.
T
he
f
ut
ur
e
of
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on
w
il
l
be
c
ha
r
a
c
te
r
iz
e
d
by
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
A
r
ti
f
I
nt
e
ll
I
S
S
N
:
2252
-
8938
A
ppl
ic
at
io
n of
t
he
adapti
v
e
ne
ur
o
-
fu
z
z
y
i
nf
e
r
e
nc
e
s
y
s
te
m
f
or
pr
e
di
c
ti
on
…
(
Y
oga T
r
i
N
ugr
aha)
1791
a
dva
nc
e
m
e
nt
s
in
te
c
hnol
ogy,
in
c
r
e
a
s
e
d
us
e
of
r
e
ne
w
a
bl
e
r
e
s
our
c
e
s
,
a
nd
th
e
in
te
gr
a
ti
on
of
in
nova
ti
ve
s
ol
ut
io
ns
t
o c
r
e
a
te
a
r
e
s
il
ie
nt
a
nd s
us
t
a
in
a
bl
e
e
ne
r
gy s
y
s
te
m
[
5]
.
T
he
f
ut
ur
e
of
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on
i
s
poi
s
e
d
f
or
s
i
gni
f
ic
a
nt
tr
a
ns
f
or
m
a
ti
on,
dr
iv
e
n
by
te
c
hnol
ogi
c
a
l
in
nova
ti
on,
e
nvi
r
onm
e
nt
a
l
im
pe
r
a
ti
ve
s
,
a
nd
e
vol
vi
ng
e
ne
r
gy
de
m
a
nds
.
A
s
th
e
w
or
ld
gr
a
ppl
e
s
w
it
h
th
e
c
ha
ll
e
nge
s
of
c
li
m
a
te
c
ha
nge
a
nd
f
in
it
e
f
os
s
il
f
ue
l
r
e
s
our
c
e
s
,
th
e
e
n
e
r
gy
s
e
c
to
r
is
s
hi
f
ti
ng
to
w
a
r
ds
m
or
e
s
us
ta
in
a
bl
e
a
nd
e
f
f
ic
ie
nt
m
e
a
n
s
of
ge
ne
r
a
ti
ng
e
le
c
tr
ic
it
y
[
6]
.
P
r
e
di
c
ti
ng
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on
is
c
r
uc
ia
l
f
or
va
r
io
us
in
dus
tr
ie
s
a
nd
pol
ic
ym
a
ke
r
s
to
e
ns
ur
e
e
f
f
ic
ie
nt
r
e
s
our
c
e
a
ll
oc
a
ti
on
a
nd
m
e
e
t
e
ne
r
gy
de
m
a
nds
[
7]
.
W
it
h
th
e
a
dve
nt
of
r
e
ne
w
a
bl
e
e
ne
r
gy
s
our
c
e
s
[
8]
li
ke
s
ol
a
r
,
w
in
d,
a
nd
hydr
oe
le
c
tr
ic
pow
e
r
,
a
c
c
ur
a
te
pr
e
di
c
ti
on
be
c
om
e
s
e
ve
n
m
or
e
c
r
it
ic
a
l
due
to
th
e
ir
in
te
r
m
it
te
nt
na
tu
r
e
[
9
]
.
I
n
th
is
r
e
s
e
a
r
c
h
ba
c
kgr
ound,
w
e
'
ll
di
s
c
us
s
th
e
im
por
ta
nc
e
of
pr
e
di
c
ti
ng
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on,
th
e
c
ha
ll
e
nge
s
in
vol
ve
d,
a
nd t
he
m
e
th
ods
c
om
m
onl
y e
m
pl
oye
d f
or
a
c
c
ur
a
te
pr
e
di
c
ti
on
[
10]
.
T
he
e
l
e
c
tr
ic
it
y
de
m
a
nd
c
ont
in
ue
s
to
r
is
e
gl
oba
ll
y
e
s
pe
c
ia
ll
y
i
n
J
a
ka
r
ta
.
J
a
ka
r
ta
,
th
e
c
a
pi
ta
l
c
it
y
of
I
ndone
s
ia
,
is
a
r
a
pi
dl
y
gr
ow
in
g
ur
ba
n
a
r
e
a
w
it
h
a
bur
ge
oni
n
g
popula
ti
on
a
nd
e
s
c
a
la
ti
ng
e
ne
r
gy
de
m
a
nd
s
.
M
e
e
ti
ng
th
e
s
e
de
m
a
nd
s
w
hi
le
m
a
na
gi
ng
e
nvi
r
onm
e
nt
a
l
s
us
ta
in
a
bi
li
ty
a
nd
gr
id
s
ta
bi
li
ty
is
a
s
ig
ni
f
ic
a
nt
c
ha
ll
e
nge
.
T
h
e
c
it
y'
s
e
n
e
r
gy
pr
oduc
ti
on
is
a
c
om
pl
e
x
m
ix
of
tr
a
di
ti
ona
l
a
nd
r
e
ne
w
a
bl
e
e
ne
r
gy
s
our
c
e
s
,
in
f
lu
e
nc
e
d
by
va
r
io
us
f
a
c
to
r
s
in
c
lu
di
ng
popula
ti
on
gr
ow
th
,
e
c
onomi
c
a
c
ti
vi
ti
e
s
,
a
nd
c
li
m
a
ti
c
c
ondi
ti
ons
.
H
ow
e
ve
r
,
th
e
ge
ne
r
a
ti
on
of
e
le
c
tr
ic
it
y
r
e
li
e
s
on
va
r
io
us
f
a
c
to
r
s
,
in
c
lu
di
ng
w
e
a
th
e
r
c
ondi
ti
ons
,
f
ue
l
a
va
il
a
bi
li
ty
,
a
nd
in
f
r
a
s
tr
uc
tu
r
e
c
a
pa
bi
li
ti
e
s
.
W
it
h
th
e
in
te
gr
a
ti
on
of
r
e
ne
w
a
bl
e
e
ne
r
gy
s
our
c
e
s
in
to
th
e
gr
id
,
pr
e
di
c
ti
ng
e
ne
r
gy
pr
oduc
ti
on
be
c
om
e
s
in
he
r
e
nt
ly
m
or
e
c
om
pl
e
x
due
to
th
e
ir
de
pe
nde
n
c
e
on
w
e
a
th
e
r
pa
tt
e
r
ns
,
w
hi
c
h
a
r
e
of
te
n
unpr
e
di
c
ta
bl
e
.
T
h
e
r
e
f
or
e
,
it
is
ve
r
y
im
por
ta
nt
to
pr
e
di
c
t
th
e
pr
oduc
ti
on
of
e
le
c
tr
ic
it
y
to
de
ve
lo
p
a
pl
a
n
to
de
ve
lo
p
th
e
e
le
c
tr
ic
it
y
s
ys
te
m
in
J
a
ka
r
ta
.
T
o
s
uppor
t
th
e
pl
a
nni
ng,
w
e
ne
e
d
a
n
a
ppr
opr
ia
te
m
e
th
od
f
or
th
e
c
a
l
c
ul
a
ti
on.
T
h
e
obj
e
c
ti
ve
of
th
is
pr
opos
e
d
r
e
s
e
a
r
c
h
is
to
de
ve
lo
p
a
pr
e
di
c
ti
ve
m
ode
l
u
s
in
g
th
e
a
da
pt
iv
e
ne
ur
o
-
f
uz
z
y
in
f
e
r
e
nc
e
s
ys
te
m
(
A
N
F
I
S
)
f
or
th
e
pr
e
di
c
ti
on
of
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on
in
J
a
ka
r
ta
.
T
hi
s
m
ode
l
w
il
l
he
lp
in
opt
im
iz
in
g
e
ne
r
gy
pr
oduc
ti
on
w
he
r
e
pr
e
vi
ous
r
e
s
e
a
r
c
h
us
e
d
th
e
r
e
gr
e
s
s
io
n
m
e
th
od
in
th
e
S
im
pl
e
E
a
ppl
ic
a
ti
on
,
w
h
e
r
e
th
e
pr
e
di
c
ti
on
r
e
s
ul
ts
ha
ve
a
gr
e
a
te
r
e
r
r
or
r
a
te
th
a
n
th
e
a
c
tu
a
l
r
e
s
ul
t
s
.
S
o,
th
is
r
e
s
e
a
r
c
h
u
s
e
s
th
e
A
N
F
I
S
m
e
t
hod
s
o
t
h
a
t
t
h
e
A
N
F
I
S
p
r
e
di
c
ti
on r
e
s
u
lt
s
h
a
v
e
a
s
m
a
ll
e
r
r
or
f
r
om
th
e
a
c
tu
a
l
r
e
s
u
lt
s
.
2.
M
E
T
H
O
D
E
le
c
tr
ic
a
l
e
ne
r
gy
is
e
s
s
e
nt
ia
l
f
or
pol
ic
ym
a
ke
r
s
,
e
ngi
ne
e
r
s
,
r
e
s
e
a
r
c
he
r
s
,
a
nd
c
ons
um
e
r
s
to
m
a
k
e
in
f
or
m
e
d
de
c
is
io
ns
r
e
ga
r
di
ng
e
ne
r
gy
pr
oduc
ti
on,
c
ons
um
pt
io
n,
a
nd
s
us
ta
in
a
bi
li
ty
.
T
hi
s
unde
r
li
e
s
e
f
f
or
ts
to
tr
a
ns
it
io
n
to
w
a
r
ds
a
c
le
a
ne
r
a
nd
m
or
e
e
f
f
ic
ie
nt
e
ne
r
gy
s
ys
te
m
,
e
ns
ur
in
g
a
r
e
li
a
bl
e
e
le
c
tr
ic
it
y
s
uppl
y
w
hi
le
m
in
im
iz
in
g
e
nvi
r
onm
e
nt
a
l
im
pa
c
ts
a
nd
in
c
r
e
a
s
in
g
e
c
onomi
c
be
ne
f
it
s
.
C
ont
in
ue
d
a
dva
nc
e
s
in
te
c
hnol
ogy
a
nd
pol
ic
y
f
r
a
m
e
w
or
ks
a
r
e
c
r
it
ic
a
l
to
a
c
hi
e
vi
ng
a
s
us
ta
in
a
bl
e
e
ne
r
g
y
f
ut
ur
e
gl
oba
ll
y.
E
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
o
n
is
a
m
ul
ti
f
a
c
e
te
d
pr
oc
e
s
s
e
nc
om
pa
s
s
in
g
ge
n
e
r
a
ti
on
f
r
om
di
ve
r
s
e
s
our
c
e
s
,
e
f
f
ic
ie
nt
tr
a
ns
m
is
s
io
n
a
nd
di
s
tr
ib
ut
io
n,
a
nd
c
ons
um
pt
io
n
a
c
r
os
s
va
r
io
us
s
e
c
to
r
s
.
T
he
e
vol
ut
io
n
to
w
a
r
ds
s
us
ta
in
a
bl
e
e
ne
r
gy
s
ys
te
m
s
in
vol
ve
s
in
te
gr
a
ti
ng
r
e
ne
w
a
bl
e
e
ne
r
gy
s
our
c
e
s
,
e
nh
a
nc
in
g
gr
id
r
e
li
a
bi
li
ty
th
r
ough
s
m
a
r
t
te
c
hnol
ogi
e
s
,
a
nd
a
ddr
e
s
s
in
g
e
nvi
r
onm
e
nt
a
l
a
nd
ope
r
a
ti
ona
l
c
h
a
ll
e
nge
s
[
11]
.
A
s
gl
oba
l
e
ne
r
gy
de
m
a
nd
gr
ow
s
,
in
nova
ti
on,
pol
ic
y
s
uppor
t,
a
nd
in
te
r
na
ti
ona
l
c
oope
r
a
ti
on
w
il
l
be
pi
vot
a
l
in
s
ha
pi
ng
a
r
e
s
il
ie
nt
a
nd
s
us
t
a
in
a
bl
e
f
ut
ur
e
f
or
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on
w
or
ld
w
id
e
[
12
]
.
T
o
pr
e
di
c
t
e
le
c
tr
i
c
a
l
e
ne
r
gy
pr
oduc
ti
on
in
J
a
ka
r
ta
,
w
e
c
a
n
us
e
a
da
ta
-
dr
iv
e
n
a
ppr
oa
c
h
in
vol
vi
ng
s
ta
ti
s
ti
c
a
l
m
od
e
li
ng,
a
r
ti
f
ic
ia
l
i
nt
e
ll
ig
e
nc
e
a
nd
m
a
c
hi
ne
l
e
a
r
ni
ng
te
c
hni
que
s
.
I
n
th
is
r
e
s
e
a
r
c
h,
th
e
da
ta
-
ba
s
e
d
a
ppr
oa
c
h
m
e
th
od
us
e
d
is
A
N
F
I
S
.
T
he
A
N
F
I
S
m
ode
l
c
a
n
be
us
e
d
to
pr
e
di
c
t
f
ut
ur
e
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on
ba
s
e
d
on
ne
w
in
put
da
ta
.
A
N
F
I
S
m
ode
ls
r
e
qui
r
e
s
uf
f
ic
ie
nt
da
ta
f
o
r
a
c
c
ur
a
te
pr
e
di
c
ti
ons
.
E
ns
ur
e
th
e
da
ta
s
e
t
is
r
e
pr
e
s
e
nt
a
ti
ve
a
nd
c
ove
r
s
a
w
id
e
r
a
nge
of
s
c
e
na
r
io
s
a
s
li
ke
a
s
f
ue
l
c
ons
um
pt
io
n, e
c
onomi
c
s
, popula
ti
on, a
nd i
ndu
s
tr
y.
T
hi
s
s
e
c
ti
on
w
il
l
e
xpl
a
in
a
bout
th
e
s
te
ps
of
th
e
pr
oc
e
s
s
of
th
e
c
our
s
e
of
r
e
s
e
a
r
c
h.
T
he
s
te
ps
of
th
is
r
e
s
e
a
r
c
h
pr
oc
e
s
s
be
gi
n
w
it
h a
s
tu
dy
of
th
e
pr
e
vi
ou
s
r
e
s
e
a
r
c
h
li
te
r
a
tu
r
e
us
in
g
th
e
A
N
F
I
S
a
nd
s
om
e
pa
r
a
m
e
te
r
s
us
e
d
a
s
in
put
da
ta
f
or
th
is
r
e
s
e
a
r
c
h.
T
he
s
te
p
s
of
th
e
r
e
s
e
a
r
c
h
pr
oc
e
s
s
c
a
n
be
s
e
e
n
in
F
ig
ur
e
1.
F
ig
ur
e
1
e
xpl
a
in
s
th
e
s
te
p
s
of
th
e
r
e
s
e
a
r
c
h
pr
oc
e
s
s
u
s
in
g
th
e
A
N
F
I
S
te
c
hni
que
.
W
he
r
e
A
N
F
I
S
is
a
hybr
id
c
om
put
in
g
m
e
th
odol
ogy
th
a
t
in
te
gr
a
te
s
th
e
p
r
in
c
ip
le
s
of
f
uz
z
y
lo
gi
c
a
nd
ne
ur
a
l
ne
twor
ks
[
13
]
.
M
A
T
L
A
B
pr
ovi
de
s
a
c
om
pr
e
he
ns
iv
e
e
nvi
r
onm
e
nt
f
or
im
pl
e
m
e
nt
in
g
A
N
F
I
S
m
ode
l
s
due
to
it
s
bui
lt
-
in
f
unc
ti
ons
a
nd
to
ol
boxe
s
s
pe
c
if
ic
a
ll
y
de
s
ig
ne
d
f
or
f
uz
z
y
lo
gi
c
a
nd
ne
ur
a
l
ne
twor
ks
[
14]
.
M
e
th
odol
ogy
f
or
i
m
pl
e
m
e
nt
in
g
A
N
F
I
S
us
in
g
M
A
T
L
A
B
[
15]
.
S
ta
r
t
by
c
ol
le
c
ti
ng
or
obt
a
in
in
g
hi
s
to
r
ic
a
l
da
ta
r
e
le
va
nt
to
th
e
pr
obl
e
m
w
a
nt
to
m
ode
l.
E
ns
ur
e
th
a
t
th
e
da
ta
is
pr
ope
r
ly
f
or
m
a
tt
e
d
a
nd
p
r
e
pr
oc
e
s
s
e
d,
in
c
lu
di
ng
ha
ndl
in
g
m
is
s
in
g
va
lu
e
s
,
s
c
a
li
ng,
a
nd
nor
m
a
li
z
a
ti
on
if
ne
c
e
s
s
a
r
y.
D
e
s
ig
n
th
e
a
r
c
hi
te
c
tu
r
e
of
th
e
A
N
F
I
S
m
ode
l
[
16]
.
D
e
te
r
m
in
e
th
e
num
be
r
of
in
pu
t
va
r
ia
bl
e
s
,
m
e
m
be
r
s
hi
p
f
unc
ti
ons
,
r
ul
e
s
,
a
nd
out
put
va
r
ia
bl
e
s
ba
s
e
d
on
th
e
c
ha
r
a
c
te
r
is
ti
c
s
of
pr
obl
e
m
[
17]
.
M
A
T
L
A
B
pr
ovi
de
s
f
unc
ti
ons
f
or
c
r
e
a
ti
ng f
uz
z
y i
nf
e
r
e
nc
e
s
ys
te
m
s
a
nd de
f
in
in
g m
e
m
be
r
s
hi
p f
unc
ti
ons
[
18]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
. 14, No. 3, J
une
20
25
:
1790
-
1798
1792
F
ig
ur
e
1. T
he
s
te
p of
t
he
r
e
s
e
a
r
c
h pr
oc
e
s
s
D
iv
id
e
th
e
da
ta
s
e
t
in
to
s
e
ts
f
or
te
s
ti
ng,
va
li
da
ti
on,
a
nd
tr
a
in
in
g
.
T
he
A
N
F
I
S
m
ode
l
is
tr
a
in
e
d
us
in
g
th
e
tr
a
in
in
g
s
e
t,
pa
r
a
m
e
te
r
s
a
r
e
a
dj
us
te
d
a
nd
ove
r
f
it
ti
ng
is
pr
e
ve
nt
e
d
us
in
g
th
e
va
li
da
ti
on
s
e
t,
a
nd
th
e
tr
a
in
e
d
m
ode
l'
s
pe
r
f
or
m
a
nc
e
is
a
s
s
e
s
s
e
d
us
in
g
th
e
te
s
ti
ng
s
e
t
[
19]
.
T
r
a
in
th
e
A
N
F
I
S
m
ode
l
us
in
g
th
e
tr
a
in
in
g
da
ta
.
M
A
T
L
A
B
pr
ovi
de
s
f
unc
ti
on
s
s
uc
h
a
s
'
a
nf
is
'
or
'
ge
nf
is
'
f
or
tr
a
in
in
g
A
N
F
I
S
m
ode
ls
[
20]
.
S
pe
c
if
y
pa
r
a
m
e
te
r
s
s
uc
h a
s
t
he
numb
e
r
of
e
poc
hs
, l
e
a
r
ni
ng r
a
te
, a
nd opti
m
iz
a
ti
on a
l
gor
it
hm
s
dur
in
g t
r
a
in
in
g.
V
a
li
da
te
th
e
tr
a
in
e
d
A
N
F
I
S
m
ode
l
us
in
g
th
e
va
li
da
ti
on
da
ta
s
e
t
to
e
ns
ur
e
th
a
t
it
ge
ne
r
a
li
z
e
s
w
e
ll
to
uns
e
e
n
da
ta
.
A
dj
us
t
m
ode
l
pa
r
a
m
e
te
r
s
if
ne
c
e
s
s
a
r
y,
ba
s
e
d
o
n
va
li
da
ti
on
pe
r
f
or
m
a
nc
e
[
21]
.
T
e
s
t
th
e
f
in
a
l
A
N
F
I
S
m
ode
l
us
in
g
th
e
te
s
ti
ng
da
ta
s
e
t
to
e
va
lu
a
te
it
s
pe
r
f
or
m
a
nc
e
a
nd
a
s
s
e
s
s
it
s
a
c
c
ur
a
c
y
in
pr
e
di
c
ti
ng
out
put
s
.
U
s
e
r
e
le
va
nt
m
e
a
s
ur
e
s
,
s
uc
h
a
s
m
e
a
n
s
qua
r
e
d
e
r
r
or
(
M
S
E
)
,
r
oot
m
e
a
n
s
qua
r
e
e
r
r
or
(
R
M
S
E
)
,
o
r
c
oe
f
f
ic
ie
nt
of
de
te
r
m
in
a
ti
on,
to
a
s
s
e
s
s
th
e
A
N
F
I
S
m
ode
l'
s
p
e
r
f
or
m
a
nc
e
.
T
o
unde
r
s
ta
nd
how
th
e
A
N
F
I
S
m
ode
l
pr
e
di
c
ts
,
vi
s
ua
li
z
e
th
e
in
put
-
out
put
li
nka
ge
s
,
m
e
m
be
r
s
hi
p
f
unc
ti
ons
,
a
nd
r
ul
e
a
c
ti
va
ti
on.
P
lo
tt
in
g
f
unc
ti
ons
f
or
f
uz
z
y i
nf
e
r
e
nc
e
s
ys
te
m
s
a
nd n
e
ur
a
l
ne
twor
ks
a
r
e
a
va
il
a
bl
e
i
n M
A
T
L
A
B
.
2.1.
A
N
F
I
S
T
he
A
N
F
I
S
is
a
hybr
id
in
te
ll
ig
e
nt
s
ys
te
m
th
a
t
c
om
bi
ne
s
th
e
c
a
pa
bi
li
ti
e
s
of
f
uz
z
y
lo
gi
c
a
nd
ne
ur
a
l
ne
twor
ks
to
pe
r
f
or
m
ta
s
ks
s
uc
h
a
s
c
la
s
s
if
ic
a
ti
on,
r
e
gr
e
s
s
io
n,
a
nd
c
ont
r
ol
[
22]
.
T
he
le
a
r
ni
ng
pr
oc
e
s
s
is
th
e
n
c
a
r
r
ie
d
out
a
ga
in
s
t
th
e
d
a
ta
in
or
de
r
to
ge
ne
r
a
t
e
th
e
out
put
a
s
a
pr
e
di
c
ti
on
r
e
s
ul
t
[
23]
.
T
he
tr
a
in
in
g
a
lg
or
it
hm
f
or
A
N
F
I
S
is
a
hybr
id
le
a
r
ni
ng
te
c
hni
que
th
a
t
us
e
s
gr
a
di
e
nt
de
s
c
e
nt
a
nd
e
r
r
or
ba
c
kpr
opa
ga
ti
on
(
E
B
P
)
on
r
e
ve
r
s
e
s
tr
e
a
m
s
to
c
om
put
e
e
r
r
or
s
oc
c
ur
r
in
g
on
e
a
c
h
la
ye
r
,
a
nd
le
a
s
t
-
s
qua
r
e
s
e
s
ti
m
a
to
r
(
L
S
E
)
a
ppr
oa
c
h
to
de
te
r
m
in
e
c
ons
e
que
nt
va
lu
e
s
on a
dva
n
c
e
d s
tr
e
a
m
s
[
24]
.
F
iv
e
la
ye
r
s
m
a
ke
up
A
N
F
I
S
.
T
he
f
uz
z
if
ic
a
ti
on
m
e
th
od
m
a
ps
t
he
in
put
a
nd
ta
r
ge
t
da
ta
in
th
e
de
gr
e
e
of
m
e
m
be
r
s
hi
p,
c
ons
ti
tu
ti
ng
th
e
f
ir
s
t
la
ye
r
[
25]
.
T
he
in
f
e
r
e
n
c
e
pr
oc
e
dur
e
th
a
t
de
te
r
m
in
e
s
f
uz
z
y
r
ul
e
s
is
c
a
r
r
ie
d
out
by
th
e
s
e
c
ond
a
nd
th
ir
d
la
ye
r
s
us
in
g
S
uge
no
in
f
e
r
e
nc
e
,
a
nd
th
e
r
e
s
ul
ts
a
r
e
ha
ndl
e
d
in
th
e
c
om
put
a
ti
on
th
a
t
f
ol
lo
w
s
.
L
S
E
is
u
s
e
d
a
t
la
ye
r
4
to
c
onduc
t
th
e
e
ns
ui
ng
va
lu
e
s
e
a
r
c
h
pr
oc
e
dur
e
.
L
a
ye
r
5
pr
oc
e
s
s
e
s
t
he
t
w
o output
s
f
r
om
la
ye
r
4 i
n a
s
um
m
a
r
y m
a
nne
r
.
L
a
ye
r
s
1
-
4
of
A
N
F
I
S
c
ont
a
in
th
e
f
uz
z
y
in
f
e
r
e
nc
e
s
ys
te
m
,
w
hi
c
h
is
r
e
s
pons
ib
le
f
or
id
e
nt
if
yi
ng
th
e
ne
ur
a
l
ne
twor
k s
ys
te
m
'
s
hi
dde
n node
s
[
26]
. G
r
a
di
e
nt
de
s
c
e
nt
i
s
us
e
d t
o a
dj
us
t
th
e
i
nput
pa
r
a
m
e
te
r
va
lu
e
s
a
f
te
r
th
e
f
or
w
a
r
d
f
lo
w
c
om
put
a
ti
on,
a
nd
th
e
e
r
r
or
va
lu
e
f
or
e
a
c
h
la
ye
r
is
obt
a
in
e
d
by
doi
ng
a
ba
c
kw
a
r
d
f
lo
w
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
A
r
ti
f
I
nt
e
ll
I
S
S
N
:
2252
-
8938
A
ppl
ic
at
io
n of
t
he
adapti
v
e
ne
ur
o
-
fu
z
z
y
i
nf
e
r
e
nc
e
s
y
s
te
m
f
or
pr
e
di
c
ti
on
…
(
Y
oga T
r
i
N
ugr
aha)
1793
c
om
put
a
ti
on
[
27]
.
T
he
c
om
put
in
g
pr
oc
e
s
s
de
s
c
r
ib
e
d
a
bove
w
il
l
c
ont
in
ue
unt
il
th
e
e
r
r
or
va
lu
e
a
ppr
oa
c
he
s
th
e
m
a
xi
m
um
e
r
r
or
va
lu
e
t
ha
t
ha
s
be
e
n s
e
t
[
10]
.
T
he
A
N
F
I
S
us
e
d
to
pr
e
di
c
t
is
in
it
ia
li
z
e
th
e
A
N
F
I
S
pa
r
a
m
e
te
r
s
, na
m
e
ly
le
a
r
ni
ng
r
a
te
(
lr
)
,
m
om
e
nt
um
(
m
c
)
,
e
r
r
or
l
im
it
(
e
r
r
)
,
a
nd
m
a
xi
m
um
it
e
r
a
ti
on
(
m
a
x
e
poc
h
)
.
T
he
f
ir
s
t
s
ta
ge
c
a
r
r
ie
d
out
is
a
f
or
w
a
r
d
pa
th
w
hi
c
h
c
ont
a
in
s
s
e
ve
r
a
l
s
t
a
ge
s
to
f
in
d
th
e
c
on
s
e
que
nt
v
a
lu
e
of
th
e
r
ul
e
c
r
e
a
te
d
a
nd
a
dd
up
a
ll
th
e
in
put
in
th
e
la
s
t
la
ye
r
[
28]
. T
he
s
ta
ge
s
of
t
he
f
or
w
a
r
d l
a
ne
a
r
e
a
s
f
ol
lo
w
s
:
‒
L
a
ye
r
1 (
in
put
l
a
ye
r
)
:
t
hi
s
r
e
pr
e
s
e
nt
s
t
he
i
nput
va
r
ia
bl
e
s
of
t
he
s
ys
te
m
w
it
h node
f
unc
ti
ons
a
s
i
n (
1
)
.
1
,
=
µ
(
)
1
,
=
µ
−
2
(
)
(
1)
W
he
r
e
x
or
y
is
in
put
f
r
om
node
i,
A
i
or
B
i
is
a
li
ngui
s
ti
c
la
be
l
c
onne
c
te
d
to
node
i,
a
nd
O
1,
i
is
d
e
gr
e
e
of
m
e
m
be
r
s
hi
p of
a
f
uz
z
y s
e
t
w
it
h t
he
G
be
ll
c
ur
ve
f
unc
ti
on.
‒
L
a
ye
r
2
(
f
uz
z
y
la
ye
r
)
:
th
is
la
ye
r
c
om
put
e
s
th
e
de
gr
e
e
of
m
e
m
be
r
s
hi
p
f
or
e
a
c
h
in
put
va
r
ia
bl
e
to
e
a
c
h
f
uz
z
y s
e
t.
I
t
a
ppl
ie
s
f
uz
z
y l
ogi
c
ope
r
a
ti
on
s
[
29]
.
2
,
=
=
µ
(
)
µ
(
)
(
2)
‒
L
a
ye
r
3 (
nor
m
a
li
z
a
ti
on l
a
ye
r
)
:
it
no
r
m
a
li
z
e
s
t
he
m
e
m
be
r
s
hi
p gr
a
de
s
obt
a
in
e
d f
r
om
t
he
f
uz
z
y l
a
ye
r
[
30]
.
3
,
1
=
ŵ
=
ŵ
ŵ
1
+
ŵ
2
(
3)
‒
L
a
ye
r
4
(
c
ons
e
que
nt
la
ye
r
)
:
th
is
la
ye
r
c
om
put
e
s
th
e
out
put
by
c
om
bi
ni
ng
th
e
nor
m
a
li
z
e
d
m
e
m
be
r
s
hi
p
gr
a
de
s
w
it
h
pa
r
a
m
e
te
r
s
c
a
ll
e
d c
ons
e
qu
e
nt
pa
r
a
m
e
te
r
s
.
4
,
=
ŵ
=
ŵ
(
+
+
)
(
4
)
‒
L
a
ye
r
5 (
out
put
l
a
ye
r
)
:
i
t
p
r
oduc
e
s
t
he
f
in
a
l
out
put
of
t
he
A
N
F
I
S
s
ys
te
m
.
5
,
=
∑
ŵ
=
∑
ŵ
∑
ŵ
(
5)
=
(
ŵ
1
)
1
+
(
ŵ
1
)
1
+
(
ŵ
1
)
1
+
(
ŵ
2
)
2
+
(
ŵ
2
)
2
+
(
ŵ
2
)
2
(
6)
W
he
r
e
f
is
f
or
e
c
a
s
t/
pr
e
di
c
ti
on
r
e
s
ul
t
,
ŵ
1
,
ŵ
2
is
3r
d
la
ye
r
out
p
ut
va
lu
e
,
p,
q,
r
is
c
ons
e
que
nt
pa
r
a
m
e
te
r
va
lu
e
, a
nd
x
, y
is
in
d
e
pe
nde
nt
va
r
ia
bl
e
.
‒
A
f
te
r
c
a
r
r
yi
ng
out
t
r
a
in
in
g,
th
e
e
r
r
or
in
th
e
pr
e
di
c
ti
on
r
e
s
ul
ts
is
c
a
lc
ul
a
te
d
us
in
g
m
e
a
n
a
bs
ol
ut
e
pe
r
c
e
nt
a
ge
e
r
r
or
(
M
A
P
E
)
[
31]
,
[
32]
a
nd R
M
S
E
[
33]
,
th
e
f
o
ll
ow
in
g i
s
t
he
f
or
m
ul
a
us
e
d
:
=
∑
|
(
−
′
)
2
|
=
1
(
7)
=
√
∑
(
−
′
)
2
=
1
(
8)
W
he
r
e
y
i
is
a
c
tu
a
l
va
lu
e
of
e
le
c
tr
ic
a
l
e
n
e
r
gy
pr
oduc
ti
on,
y
i
’
is
pr
e
di
c
te
d
va
lu
e
of
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on
, a
nd
n
is
num
be
r
of
obs
e
r
va
ti
ons
.
3.
R
E
S
U
L
T
S
A
N
D
D
I
S
C
U
S
S
I
O
N
T
he
J
a
k
a
r
ta
r
e
gi
on
ye
a
r
ly
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on,
popula
t
io
n,
e
c
onomy
(
G
R
D
B
)
,
in
dus
tr
y
,
a
nd
f
os
s
il
f
ue
l
us
a
ge
f
r
om
2017
to
2022
w
e
r
e
ut
il
i
z
e
d
to
a
s
s
e
s
s
th
e
s
ugge
s
te
d
A
N
F
I
S
e
f
f
e
c
ti
ve
ne
s
s
(
s
e
e
T
a
bl
e
1)
.
I
n
to
ta
l
th
e
r
e
a
r
e
5
a
nnu
a
l
da
ta
a
nd
dur
in
g
th
e
e
xp
e
r
im
e
nt
it
c
ons
is
ts
of
117
pa
r
a
m
e
t
e
r
s
,
6
pa
ir
s
of
tr
a
in
in
g
da
ta
, 0 c
he
c
ki
ng da
ta
,
a
nd 81
f
uz
z
y
r
ul
e
s
. W
e
us
e
d
M
A
T
L
A
B
t
ool
s
t
o r
un t
he
e
xpe
r
im
e
nt
s
.
To
e
na
bl
e
th
e
a
lg
or
it
hm
to
r
e
c
ogni
z
e
th
e
da
ta
in
T
a
bl
e
1,
th
e
f
i
r
s
t
r
ound
of
pr
e
-
pr
oc
e
s
s
in
g
is
c
a
r
r
ie
d
out
.
O
ne
of
th
e
s
im
pl
e
s
t
w
a
ys
to
pr
e
pr
oc
e
s
s
da
ta
is
to
di
vi
de
a
ll
hi
s
to
r
ic
a
l
da
ta
by
a
c
ons
ta
nt
,
a
nd
th
e
n,
w
he
n
m
a
ki
ng
a
pr
e
di
c
ti
on,
r
e
tu
r
n
th
e
d
a
ta
to
it
s
or
ig
in
a
l
va
lu
e
.
T
he
da
ta
c
ont
a
in
e
d
in
T
a
bl
e
1
w
il
l
be
e
nt
e
r
e
d
in
to
th
e
A
N
F
I
S
s
tr
uc
tu
r
e
f
or
m
w
hi
c
h
c
a
n
be
s
e
e
n
in
F
ig
ur
e
2.
A
N
F
I
S
ge
ne
r
a
te
s
193
node
s
,
81
li
ne
a
r
pa
r
a
m
e
te
r
s
,
a
nd 36 non
-
li
ne
a
r
pa
r
a
m
e
te
r
s
, a
s
s
how
n i
n F
ig
ur
e
3. T
he
s
e
r
e
s
u
lt
s
s
houl
d be
s
how
n i
n F
ig
ur
e
3.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
. 14, No. 3, J
une
20
25
:
1790
-
1798
1794
T
a
bl
e
1
.
Y
e
a
r
ly
e
le
c
tr
ic
a
l
e
ne
r
gy pr
oduc
ti
on (
GW
h)
, popula
ti
on
, e
c
onomy (
G
R
D
B
)
, i
ndus
tr
y a
nd f
os
s
il
f
ue
l
us
a
ge
f
r
om
2017 to 2022 J
a
ka
r
ta
r
e
gi
on
Y
e
a
r
2017
2018
2019
2020
2021
2022
E
l
e
c
t
r
i
c
a
l
e
ne
r
gy
pr
oduc
t
i
on (
G
W
h)
36
,
365
38
,
988
41
,
284
44
,
119
47
,
039
49
,
647
P
opul
a
t
i
on (
m
i
l
l
i
on pe
opl
e
)
10
,
374
10
,
467
10
,
557
10
,
562
10
,
644
10
,
640
E
c
onom
i
c
s
(
G
R
D
B
)
1
,
635.35
1
,
735.20
1
,
836.24
1
,
792.40
1
,
856.30
1
,
453.32
I
ndus
t
r
y
2
,
582
2
,
118
1
,
792
1
,
825
1
,
628
559
F
os
s
i
l
f
ue
l
us
a
ge
164.2
165.7
176.0
188.3
204.2
218.2
F
ig
ur
e
2.
T
he
s
tr
uc
tu
r
e
of
A
N
F
I
S
F
ig
ur
e
3. F
uz
z
y r
ul
e
s
T
he
f
uz
z
y
r
ul
e
s
a
r
e
de
pi
c
te
d
in
F
ig
ur
e
3,
w
he
r
e
by
53
r
ul
e
s
a
r
e
f
or
m
e
d
ba
s
e
d
on
te
s
ti
ng
a
nd
e
xpe
r
im
e
nt
a
ti
on
w
it
h
da
ta
on
pow
e
r
pr
oduc
ti
on
pr
oj
e
c
ti
ons
f
or
th
e
pr
ovi
nc
e
of
J
a
ka
r
ta
.
W
e
obt
a
in
e
d
1
f
uz
z
y
r
ul
e
w
it
h c
or
r
e
c
t
r
e
s
ul
ts
out
of
53 r
ul
e
s
ge
ne
r
a
te
d by f
uz
z
y, w
hi
c
h i
s
t
he
41s
t
f
uz
z
y r
ul
e
. T
he
r
e
f
or
e
, w
e
ha
d a
n
in
a
c
c
ur
a
c
y
of
0.0001058%
w
he
n
w
e
te
s
te
d
th
e
da
ta
.
F
ig
ur
e
4
s
how
s
th
e
r
e
s
ul
ts
of
th
e
s
e
m
is
t
a
ke
s
.
T
he
pr
e
di
c
ti
on
r
e
s
ul
ts
of
th
e
A
N
F
I
S
ha
ve
a
ve
r
y
ti
ny
e
r
r
o
r
va
lu
e
w
it
h
th
e
a
c
tu
a
l
da
ta
,
a
s
s
how
n
in
F
ig
ur
e
4.
T
he
pr
e
di
c
te
d va
lu
e
r
e
s
ul
ts
f
or
e
le
c
tr
ic
a
l
e
ne
r
gy pr
oduc
ti
on i
n J
a
k
a
r
ta
i
n 2022
-
2028 c
a
n be
s
how
n i
n
T
a
bl
e
2.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
A
r
ti
f
I
nt
e
ll
I
S
S
N
:
2252
-
8938
A
ppl
ic
at
io
n of
t
he
adapti
v
e
ne
ur
o
-
fu
z
z
y
i
nf
e
r
e
nc
e
s
y
s
te
m
f
or
pr
e
di
c
ti
on
…
(
Y
oga T
r
i
N
ugr
aha)
1795
T
a
bl
e
2.
P
r
e
di
c
ti
on r
e
s
ul
ts
f
or
J
a
ka
r
ta
r
e
gi
on e
le
c
tr
ic
a
l
e
ne
r
gy p
r
oduc
ti
on f
r
om
2022
-
2028
Y
e
a
r
2022
2023
2024
2025
2026
2027
2028
P
r
e
di
c
t
i
on r
e
s
ul
t
s
of
e
l
e
c
t
r
i
c
a
l
e
ne
r
gy pr
oduc
t
i
on (
G
W
h)
w
i
t
h
R
M
S
E
0.0001058%
49
,
647
53
,
253
54
,
860
57
,
467
60
,
074
62
,
681
65
,
288
P
r
e
di
c
t
i
on r
e
s
ul
t
s
of
e
l
e
c
t
r
i
c
a
l
e
ne
r
gy (
G
W
h)
w
i
t
h M
A
P
E
0.00875%
49
,
642
52
,
250
54
,
858
57
,
466
60
,
074
62
,
682
65
,
290
P
r
e
di
c
t
i
on r
e
s
ul
t
s
of
e
l
e
c
t
r
i
c
a
l
e
ne
r
gy (
G
W
h)
f
r
om
P
L
N
49
,
647
44
,
315
46
,
395
48
,
544
51
,
025
53
,
623
56
,
358
F
ig
ur
e
4. A
N
F
I
S
r
e
s
ul
ts
F
r
om
th
e
T
a
bl
e
2,
th
e
c
a
lc
ul
a
ti
on
s
pr
oduc
e
d
by
th
e
A
N
F
I
S
m
e
th
od
ha
ve
a
R
M
S
E
va
lu
e
=
0.0001058%
w
hi
le
th
e
M
A
P
E
va
lu
e
i
s
=
0.00875%
.
S
o,
th
e
r
e
s
ul
ts
of
th
is
A
N
F
I
S
m
e
th
od
ha
ve
s
m
a
ll
e
r
r
or
s
f
r
om
th
e
a
c
tu
a
l
r
e
s
ul
ts
a
nd
ha
ve
a
gr
ow
th
in
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on
in
J
a
ka
r
ta
of
5.25%
e
ve
r
y
ye
a
r
f
r
om
th
e
a
c
tu
a
l
da
ta
.
M
e
a
nw
hi
le
,
th
e
pr
e
di
c
ti
on
r
e
s
ul
ts
m
a
de
by
P
T
.
P
L
N
(
P
e
r
s
e
r
o)
r
e
ga
r
di
ng
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on
us
e
s
S
im
pl
e
E
a
ppl
ic
a
ti
on
w
e
r
e
4.80%
.
S
o,
f
r
om
th
e
r
e
s
ul
ts
s
how
n
in
T
a
bl
e
2,
it
w
il
l
be
pr
e
s
e
nt
e
d
in
F
ig
ur
e
5
w
hi
c
h
is
a
c
om
pa
r
is
on
of
th
e
r
e
s
ul
ts
of
A
N
F
I
S
pr
e
di
c
ti
ons
,
pr
e
di
c
ti
ons
f
r
om
P
T
.
P
L
N
(
P
e
r
s
e
r
o)
w
it
h
a
c
tu
a
l
da
ta
.
F
r
om
th
e
pr
e
di
c
ti
on
r
e
s
ul
ts
is
s
ue
d
by
A
N
F
I
S
a
c
c
or
di
ng
to
F
ig
ur
e
5,
th
e
a
ut
hor
s
ugge
s
ts
to
P
T
.
P
L
N
(
P
e
r
s
e
r
o)
to
us
e
th
is
m
e
th
od,
be
c
a
us
e
th
is
m
e
th
od
pr
ovi
de
s
ve
r
y
pr
e
c
is
e
a
nd
a
c
c
ur
a
te
r
e
s
ul
ts
a
nd ha
s
v
e
r
y s
m
a
ll
e
r
r
or
s
.
F
ig
ur
e
5. T
he
c
om
pa
r
is
on of
t
he
r
e
s
ul
ts
of
A
N
F
I
S
pr
e
di
c
ti
ons
, pr
e
di
c
ti
ons
f
r
om
P
T
.
P
L
N
(
P
e
r
s
e
r
o)
w
it
h
a
c
tu
a
l
da
ta
0
10
20
30
40
50
60
70
2
0
2
2
2
0
2
3
2
0
2
4
2
0
2
5
2
0
2
6
2
0
2
7
2
0
2
8
E
l
e
c
t
ri
c
a
l
e
n
e
rgy
p
ro
d
u
c
t
i
o
n
(
Gw
h
)
Y
ea
r
s
A
N
F
IS
P
r
ed
i
c
t
i
o
n
R
es
u
l
t
(
R
M
S
E
)
A
N
F
IS
P
r
e
d
i
c
t
i
o
n
R
e
s
u
l
t
(
M
A
P
E
)
P
T
.
P
L
N
(
P
er
s
er
o
)
P
r
ed
i
c
t
i
o
n
R
es
u
l
t
A
c
t
u
a
l
D
a
t
a
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
. 14, No. 3, J
une
20
25
:
1790
-
1798
1796
4.
C
O
N
C
L
U
S
I
O
N
T
he
pr
o
duc
ti
on
of
e
le
c
tr
ic
a
l
e
n
e
r
gy
is
a
t
a
pi
vot
a
l
ju
nc
tu
r
e
,
dr
iv
e
n
by
th
e
n
e
e
d
f
or
s
us
t
a
in
a
bl
e
pr
a
c
ti
c
e
s
,
t
e
c
hn
ol
ogi
c
a
l
a
dv
a
nc
e
m
e
nt
s
,
a
n
d
in
c
r
e
a
s
in
g
gl
ob
a
l
e
n
e
r
gy
d
e
m
a
n
ds
.
A
s
li
k
e
a
s
J
a
k
a
r
ta
,
th
e
f
ut
ur
e
of
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
odu
c
ti
on
hi
nge
s
on
b
a
la
nc
in
g
r
e
li
a
b
le
s
uppl
y,
e
nvi
r
o
nm
e
nt
a
l
s
us
t
a
in
a
bi
li
ty
,
a
nd
e
c
on
om
ic
vi
a
bi
li
ty
.
J
a
ka
r
t
a
,
I
nd
one
s
ia
’
s
c
a
pi
t
a
l,
a
nd
a
dyna
m
ic
m
e
tr
opo
li
s
f
a
c
e
s
s
i
gni
f
ic
a
nt
c
ha
ll
e
ng
e
s
i
n
m
e
e
ti
ng
i
ts
gr
ow
in
g
e
ne
r
gy
d
e
m
a
n
ds
w
hi
l
e
a
ddr
e
s
s
i
ng
e
nvi
r
onm
e
nt
a
l
a
n
d
in
f
r
a
s
tr
uc
t
ur
a
l
c
on
c
e
r
n
s
.
T
h
e
c
it
y'
s
c
ur
r
e
nt
e
ne
r
gy
m
ix
pr
e
dom
in
a
nt
ly
r
e
li
e
s
on
f
o
s
s
il
f
ue
l
s
,
w
it
h
a
gr
o
w
in
g
but
s
ti
ll
li
m
it
e
d
c
ont
r
ib
ut
i
on
f
r
om
r
e
n
e
w
a
bl
e
e
ne
r
gy
s
our
c
e
s
.
T
hi
s
r
e
s
e
a
r
c
h
pr
opo
s
e
d
on
pr
e
di
c
ti
on
of
e
le
c
tr
ic
a
l
e
n
e
r
gy
pr
odu
c
ti
on
in
J
a
ka
r
t
a
.
T
he
a
ppl
ic
a
ti
on
of
t
he
A
N
F
I
S
f
or
t
he
pr
e
di
c
ti
on
of
e
le
c
tr
ic
a
l
e
ne
r
gy
pr
oduc
ti
on i
n
J
a
k
a
r
ta
of
f
e
r
s
a
s
o
phi
s
ti
c
a
te
d
a
nd
e
f
f
e
c
ti
v
e
a
ppr
oa
c
h
to
a
ddr
e
s
s
in
g
th
e
c
it
y'
s
e
ne
r
g
y
c
h
a
ll
e
n
ge
s
.
T
he
r
e
s
ul
t
s
of
c
a
lc
ul
a
ti
on
s
c
a
r
r
ie
d
o
ut
u
s
in
g
th
e
A
N
F
I
S
m
e
t
hod
obt
a
i
ne
d
a
n
R
M
S
E
of
0
.0001
058%
,
w
hi
l
e
th
e
M
A
P
E
w
a
s
0.0
0875%
.
A
nd
th
e
r
e
s
ul
t
s
of
th
e
pr
e
di
c
ti
on
a
n
a
ly
s
is
of
e
le
c
tr
ic
a
l
e
n
e
r
gy
pr
o
duc
ti
on
in
J
a
k
a
r
ta
i
n
2028
a
r
e
65
,
2
88
G
W
h
a
nd
h
a
v
e
gr
ow
th
of
5.25%
.
T
h
e
r
e
s
ul
t
s
o
bt
a
in
e
d
us
i
ng
th
e
A
N
F
I
S
m
e
th
od
ha
v
e
a
s
m
a
ll
e
r
r
or
c
om
pa
r
e
d
to
th
e
a
c
tu
a
l
r
e
s
ul
t
s
r
a
t
he
r
th
a
n t
he
pr
e
di
c
ti
on
r
e
s
ul
t
s
m
a
d
e
b
y
P
T
.
P
L
N
(
P
e
r
s
e
r
o)
us
e
s
th
e
r
e
gr
e
s
s
io
n
m
e
th
od
in
th
e
S
im
pl
e
E
a
ppl
i
c
a
t
io
n,
w
he
r
e
th
e
pr
e
di
c
ti
on
r
e
s
ul
ts
ha
v
e
a
gr
e
a
te
r
e
r
r
or
r
a
t
e
a
n
d
t
h
e
a
u
th
or
s
u
gge
s
t
s
to
P
T
.
P
L
N
(
P
e
r
s
e
r
o)
to
us
e
th
i
s
m
e
th
od,
be
c
a
u
s
e
t
hi
s
m
e
t
hod pr
ovi
de
s
ve
r
y pr
e
c
i
s
e
a
nd
a
c
c
ur
a
te
r
e
s
ul
ts
a
nd
ha
s
v
e
r
y s
m
a
ll
e
r
r
or
s
.
A
C
K
N
O
WL
E
D
G
E
M
E
N
T
S
T
he
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S
[
1]
S
. Y
. K
a
nde
m
i
r
,
M
. O
.
Y
a
yl
i
,
a
nd E
. A
c
i
kk
a
l
p, “
A
s
s
e
s
s
m
e
nt
of
e
l
e
c
t
r
i
c
e
ne
r
gy
ge
ne
r
a
t
i
on us
i
ng w
i
nd
e
ne
r
gy i
n
T
ur
ke
y,”
7t
h I
r
a
n
W
i
nd E
ne
r
gy
C
onf
e
r
e
nc
e
, I
W
E
C
2021
, 2021, doi
:
10.1109/
I
W
E
C
52400.2021.9467019.
[
2]
D
.
C
e
l
i
k,
M
.
E
.
M
e
r
a
l
,
a
nd
M
.
W
a
s
e
e
m
,
“
R
e
s
t
r
i
c
t
i
ons
a
nd
dr
i
vi
ng
f
or
c
e
s
f
or
r
e
ne
w
a
bl
e
e
ne
r
gy
pr
oduc
t
i
on
de
ve
l
opm
e
nt
a
n
d
e
l
e
c
t
r
i
c
a
l
e
ne
r
gy
de
m
a
nd
i
n
ge
ne
r
a
l
a
nd
dur
i
ng
C
O
V
I
D
-
19,”
12t
h
I
nt
e
r
nat
i
o
nal
Sy
m
pos
i
um
on
A
dv
anc
e
d
T
opi
c
s
i
n
E
l
e
c
t
r
i
c
al
E
ngi
ne
e
r
i
ng, A
T
E
E
2021
, 2021, doi
:
10.1109/
A
T
E
E
52255.2021.9425216.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
A
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ti
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ppl
ic
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ur
o
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nf
e
r
e
nc
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s
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s
te
m
f
or
pr
e
di
c
ti
on
…
(
Y
oga T
r
i
N
ugr
aha)
1797
[
3]
A
.
H
a
r
r
ouz
,
D
.
B
e
l
a
t
r
a
c
he
,
K
.
B
oul
a
l
,
I
.
C
ol
a
k,
a
nd
K
.
K
a
yi
s
l
i
,
“
S
oc
i
a
l
a
c
c
e
pt
a
nc
e
of
r
e
ne
w
a
bl
e
e
ne
r
gy
de
di
c
a
t
e
d
t
o
e
l
e
c
t
r
i
c
pr
oduc
t
i
on,”
9t
h
I
nt
e
r
nat
i
onal
C
onf
e
r
e
nc
e
on
R
e
ne
w
abl
e
E
ne
r
gy
R
e
s
e
ar
c
h
an
d
A
ppl
i
c
at
i
ons
,
I
C
R
E
R
A
2020
,
pp.
283
–
288,
2020,
doi
:
10.1109/
I
C
R
E
R
A
49962.2020.9242904.
[
4]
A
. Q
a
z
i
e
t
al
.
, “
T
ow
a
r
ds
s
us
t
a
i
n
a
bl
e
e
ne
r
gy:
a
s
ys
t
e
m
a
t
i
c
r
e
vi
e
w
of
r
e
ne
w
a
bl
e
e
ne
r
gy s
our
c
e
s
, t
e
c
hnol
ogi
e
s
, a
nd
publ
i
c
opi
ni
ons
,
”
I
E
E
E
A
c
c
e
s
s
, vol
. 7, pp. 63837
–
63851, 2019, doi
:
10.1109/
A
C
C
E
S
S
.2019.2906402.
[
5]
R
. T
.
G
i
nt
i
n
g,
Y
.
T
.
N
ug
r
a
ha
,
D
. P
.
-
A
ng
i
n
, T
.
T
. G
u
l
t
om
,
W
. P
. N
a
i
ng
go
l
a
n
,
a
n
d
D
. S
i
t
a
n
gga
ng,
“
S
ho
r
t
-
t
e
r
m
f
o
r
e
c
a
s
t
f
o
r
t
he
gr
ow
t
h
of
I
n
do
ne
s
i
a
’
s
ne
w
r
e
n
e
w
a
bl
e
e
ne
r
g
y
us
i
ng t
he
a
da
pt
i
ve
ne
u
r
o
-
f
u
z
z
y i
n
f
e
r
e
n
c
e
s
ys
t
e
m
,”
J
ur
n
al
Si
s
t
e
m
I
n
f
or
m
as
i
dan
I
l
m
u
K
om
pu
t
e
r
P
r
i
m
a
(
J
U
S
I
K
O
M
P
R
I
M
A
)
,
v
ol
. 6
,
no.
2
, p
p.
57
–
6
0,
20
23,
d
oi
:
1
0.
340
12
/
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ur
na
l
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l
m
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kom
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r
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6i
2.
347
7.
[
6]
G
.
P
e
r
ve
e
n,
M
.
R
i
z
w
a
n,
a
nd
N
.
G
o
e
l
,
“
A
n
A
N
F
I
S
-
ba
s
e
d
m
ode
l
f
or
s
ol
a
r
e
ne
r
gy
f
or
e
c
a
s
t
i
ng
a
nd
i
t
s
s
m
a
r
t
gr
i
d
a
ppl
i
c
a
t
i
on,
”
E
ngi
ne
e
r
i
ng R
e
por
t
s
, vol
. 1, no. 5, 2019, doi
:
10.1002/
e
ng2.12070.
[
7]
O
.
N
.
O
ya
khi
l
om
e
n
a
nd
A
.
S
.
E
m
e
ka
,
“
C
om
pa
r
i
ng
t
he
e
l
e
c
t
r
i
c
i
t
y
f
o
r
e
c
a
s
t
pe
r
f
or
m
a
nc
e
of
t
he
A
N
F
I
S
a
nd
t
he
L
S
S
V
M
m
ode
l
s
f
or
a
c
a
s
e
of
s
uppr
e
s
s
e
d,
”
I
nt
e
r
nat
i
onal
J
our
nal
of
R
e
s
e
a
r
c
h i
n E
ngi
ne
e
r
i
ng and Sc
i
e
nc
e
(
I
J
R
E
S)
, vol
. 11, no. 3, pp. 168
–
175, 2023.
[
8]
A
. M
. S
a
l
i
m
a
nd I
. A
l
s
youf
, “
R
e
ne
w
a
bl
e
e
ne
r
gy i
n t
he
U
ni
t
e
d A
r
a
b E
m
i
r
a
t
e
s
:
s
t
a
t
us
a
nd pot
e
nt
i
a
l
,”
2020 A
dv
anc
e
s
i
n Sc
i
e
n
c
e
an
d
E
ngi
ne
e
r
i
ng T
e
c
hnol
ogy
I
nt
e
r
nat
i
onal
C
onf
e
r
e
n
c
e
s
, A
SE
T
2020
, 2020, doi
:
10.1109/
A
S
E
T
48392.2020.9118220.
[
9]
Y
.
T
.
N
ug
r
a
ha
a
nd
M
.
I
r
w
a
nt
o,
“
M
ode
l
l
i
n
g
de
m
a
n
d
f
o
r
e
ne
r
g
y
s
o
ur
c
e
s
a
s
a
l
t
e
r
na
t
i
ve
e
n
e
r
gy
i
n
t
he
P
r
ov
i
nc
e
o
f
N
o
r
t
h
S
um
a
t
r
a
,
”
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our
n
al
o
f
R
e
n
e
w
ab
l
e
E
ne
r
g
y
,
E
l
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c
t
r
i
c
al
, a
nd
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om
pu
t
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r
E
n
gi
ne
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,
vo
l
.
2,
no
.
2,
p
p
.
8
4
-
89
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02
2,
do
i
:
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.2
910
3/
j
r
e
e
c
e
.v
2i
2
.9
278
.
[
10]
X
.
H
ua
ng,
D
.
W
u,
a
nd
B
.
B
oul
e
t
,
“
E
ns
e
m
bl
e
l
e
a
r
ni
ng
f
or
c
ha
r
gi
ng
l
oa
d
f
or
e
c
a
s
t
i
ng
of
e
l
e
c
t
r
i
c
ve
hi
c
l
e
c
ha
r
gi
ng
s
t
a
t
i
ons
,”
2020
I
E
E
E
E
l
e
c
t
r
i
c
P
ow
e
r
and E
ne
r
gy
C
onf
e
r
e
nc
e
, E
P
E
C
2020
, 2020, doi
:
10.1109/
E
P
E
C
48502.2020.9319916.
[
11]
T
um
i
r
a
n
e
t
a
l
.
,
“
T
he
m
a
s
t
e
r
pl
a
n
f
or
de
ve
l
opi
ng
e
l
e
c
t
r
i
c
i
t
y
s
ys
t
e
m
s
f
or
a
r
c
hi
pe
l
a
gi
c
a
r
e
a
by
c
ons
i
de
r
i
ng
l
oc
a
l
e
ne
r
gy
r
e
s
our
c
e
s
:
a
c
a
s
e
s
t
udy
of
M
a
l
uku
I
s
l
a
nds
,
”
P
r
oc
e
e
di
ngs
of
2019
t
he
7t
h
I
nt
e
r
nat
i
onal
C
on
f
e
r
e
nc
e
on
Sm
ar
t
E
ne
r
gy
G
r
i
d
E
ngi
ne
e
r
i
ng,
SE
G
E
2019
, pp. 290
–
293, 2019, doi
:
10.1109/
S
E
G
E
.2019.8859915.
[
12]
E
.
T
.
S
a
ye
d
e
t
al
.
,
“
A
c
r
i
t
i
c
a
l
r
e
vi
e
w
on
e
nvi
r
onm
e
nt
a
l
i
m
pa
c
t
s
of
r
e
ne
w
a
bl
e
e
ne
r
gy
s
y
s
t
e
m
s
a
nd
m
i
t
i
ga
t
i
on
s
t
r
a
t
e
gi
e
s
:
w
i
nd
,
hydr
o, bi
om
a
s
s
a
nd ge
ot
he
r
m
a
l
,”
Sc
i
e
nc
e
of
t
he
T
ot
al
E
nv
i
r
onm
e
nt
, vol
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:
10.1016/
j
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c
i
t
ot
e
nv.2020.144505.
[
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F
.
K
a
hw
a
s
h,
B
.
B
a
r
a
ka
t
,
a
nd
A
.
M
a
he
r
i
,
“
C
oupl
e
d
t
he
r
m
o
-
e
l
e
c
t
r
i
c
a
l
di
s
pa
t
c
h
s
t
r
a
t
e
gy
w
i
t
h
A
I
f
or
e
c
a
s
t
i
ng
f
or
opt
i
m
a
l
s
i
z
i
ng
of
gr
i
d
-
c
onne
c
t
e
d
hybr
i
d
r
e
ne
w
a
bl
e
e
n
e
r
gy
s
y
s
t
e
m
s
,”
E
ne
r
gy
C
onv
e
r
s
i
on
and
M
anage
m
e
nt
,
vol
.
293,
2023,
doi
:
10.1016/
j
.e
nc
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a
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[
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D
.
L
i
,
G
.
S
un,
S
.
M
i
a
o,
Y
.
G
u,
Y
. Z
ha
ng,
a
nd
S
.
H
e
,
“
A
s
hor
t
-
t
e
r
m
e
l
e
c
t
r
i
c
l
oa
d
f
or
e
c
a
s
t
m
e
t
hod
ba
s
e
d
on
i
m
pr
ove
d
s
e
que
nc
e
-
to
-
s
e
que
nc
e
G
R
U
w
i
t
h
a
da
pt
i
ve
t
e
m
por
a
l
de
pe
nde
nc
e
,”
I
nt
e
r
nat
i
onal
J
ou
r
nal
of
E
l
e
c
t
r
i
c
al
P
ow
e
r
and
E
ne
r
gy
Sy
s
t
e
m
s
,
vol
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137,
2022, doi
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j
.i
j
e
pe
s
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[
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X
.
W
u
a
nd
N
.
Z
ha
ng,
“
T
he
a
ppl
i
c
a
t
i
on
of
M
A
T
L
A
B
t
e
a
c
hi
ng
i
n
t
h
e
c
ul
t
i
va
t
i
on
of
non
-
pr
of
e
s
s
i
ona
l
qua
l
i
t
y
of
unde
r
gr
a
dua
t
e
s
,
”
2020 I
nt
e
r
nat
i
onal
C
onf
e
r
e
nc
e
on I
nf
or
m
at
i
on Sc
i
e
nc
e
and E
duc
at
i
on,
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–
581, 2020, doi
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I
C
I
S
E
51755.2020.00129.
[
16]
D
.
K
.
G
h
os
e
,
K
.
T
a
na
ya
,
A
.
S
a
hoo
,
a
nd
U
.
K
um
a
r
,
“
P
e
r
f
or
m
a
nc
e
e
va
l
ua
t
i
o
n
of
hy
br
i
d
A
N
F
I
S
m
od
e
l
f
or
f
l
o
od
pr
e
di
c
t
i
on
,”
8t
h
I
n
t
e
r
n
at
i
on
al
C
o
nf
e
r
e
nc
e
on
A
dv
anc
e
d C
om
p
ut
i
n
g a
nd
C
om
m
un
i
c
at
i
on
Sy
s
t
e
m
s
,
202
2,
do
i
:
10
.1
109
/
I
C
A
C
C
S
5
415
9.
202
2.
978
50
02.
[
17]
A
.
H
.
N
ur
c
a
hyono,
F
.
N
hi
t
a
,
D
.
S
a
e
pudi
n,
a
nd
A
.
A
di
t
s
a
ni
a
,
“
P
r
i
c
e
pr
e
di
c
t
i
o
n
of
c
hi
l
i
i
n
ba
ndung
r
e
ge
nc
y
u
s
i
ng
s
uppor
t
ve
c
t
or
m
a
c
hi
ne
(
S
V
M
)
opt
i
m
i
z
e
d
w
i
t
h
a
n
a
da
pt
i
ve
n
e
ur
o
-
f
uz
z
y
i
nf
e
r
e
nc
e
s
ys
t
e
m
(
A
N
F
I
S
)
,”
2019
7t
h
I
nt
e
r
nat
i
onal
C
onf
e
r
e
nc
e
o
n
I
nf
or
m
at
i
on and C
om
m
uni
c
at
i
on T
e
c
hnol
ogy
, I
C
oI
C
T
2019
, 2019, doi
:
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I
C
oI
C
T
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P
.
P
.
M
a
noj
,
“
F
uz
z
y
l
ogi
c
m
e
t
hodol
ogy
f
or
s
hor
t
t
e
r
m
l
oa
d
f
o
r
e
c
a
s
t
i
ng,”
I
nt
e
r
nat
i
onal
J
our
nal
of
R
e
s
e
ar
c
h
i
n
E
ngi
ne
e
r
i
ng
and
T
e
c
hnol
ogy
, vol
. 3, no. 4, pp. 322
–
328, 2014, doi
:
10.15623/
i
j
r
e
t
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.
[
19]
Y
.
K
a
s
s
a
,
J
.
H
.
Z
ha
ng,
D
.
H
.
Z
he
ng,
a
nd
D
.
W
e
i
,
“
S
hor
t
t
e
r
m
w
i
nd
pow
e
r
p
r
e
di
c
t
i
on
us
i
ng
A
N
F
I
S
,”
2016
I
E
E
E
I
nt
e
r
nat
i
onal
C
onf
e
r
e
nc
e
on P
ow
e
r
and R
e
ne
w
abl
e
E
ne
r
gy
, I
C
P
R
E
2016
, pp. 388
–
393, 2017
, doi
:
10.1109/
I
C
P
R
E
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[
20]
T
.
I
na
n
a
nd
A
. F
.
B
a
ba
,
“
P
r
e
di
c
t
i
o
n of
w
i
n
d
s
pe
e
d
us
i
n
g a
r
t
i
f
i
c
i
a
l
ne
ur
a
l
ne
t
w
o
r
k
s
a
n
d A
N
F
I
S
m
e
t
ho
ds
(
obs
e
r
va
t
i
on
b
uo
y
e
xa
m
pl
e
)
,”
202
0
I
n
nov
at
i
ons
i
n
I
n
t
e
l
l
i
ge
n
t
Sy
s
t
e
m
s
and
A
pp
l
i
c
a
t
i
o
ns
C
on
f
e
r
e
n
c
e
,
A
SY
U
2
02
0
, 2
020
,
do
i
:
10
.11
09
/
A
S
Y
U
507
17
.20
20
.92
59
894
.
[
21]
I
.
M
. E
l
-
H
a
s
no
ny,
S
. I
.
B
a
r
a
ka
t
,
a
nd
R
.
R
.
M
os
t
a
f
a
,
“
O
pt
i
m
i
z
e
d
A
N
F
I
S
m
ode
l
u
s
i
ng hy
br
i
d
m
e
t
a
h
e
u
r
i
s
t
i
c
a
l
go
r
i
t
h
m
s
f
o
r
P
a
r
ki
ns
o
n’
s
di
s
e
a
s
e
p
r
e
di
c
t
i
on
i
n
I
o
T
e
nv
i
r
on
m
e
n
t
,”
I
E
E
E
A
c
c
e
s
s
,
vo
l
.
8
, p
p.
11
92
52
–
11
927
0,
20
20,
d
oi
:
1
0.
110
9/
A
C
C
E
S
S
.
202
0.
300
56
14.
[
22]
H
. S
uy
ono
, D
. O
.
P
r
a
ba
w
a
nt
i
, M
.
S
hi
di
q
, R
.
N
.
H
a
s
a
n
a
h,
U
. W
i
b
a
w
a
,
a
n
d A
.
H
a
s
i
bu
a
n,
“
F
or
e
c
a
s
t
i
n
g o
f
w
i
n
d s
pe
e
d
i
n
M
a
l
a
n
g C
i
t
y
o
f
I
n
don
e
s
i
a
us
i
ng
a
d
a
p
t
i
v
e
ne
u
r
o
-
f
uz
z
y
i
n
f
e
r
e
nc
e
s
ys
t
e
m
a
n
d
a
ut
or
e
g
r
e
s
s
i
ve
i
n
t
e
g
r
a
t
e
d
m
o
vi
ng
a
ve
r
a
ge
m
e
t
h
ods
,
”
2
nd
I
nt
e
r
na
t
i
on
al
C
onf
e
r
e
nc
e
o
n
T
e
c
hno
l
o
gy
and
P
o
l
i
c
y
i
n
E
l
e
c
t
r
i
c
P
ow
e
r
an
d
E
ne
r
gy
,
p
p.
13
1
–
1
3
6,
202
0,
do
i
:
1
0.1
10
9/
I
C
T
-
P
E
P
50
91
6.2
02
0.9
24
986
7.
[
23]
A
.
A
.
Z
a
k
r
i
,
M
.
W
.
M
us
t
a
f
a
,
a
n
d
I
.
T
r
i
bo
w
o,
“
A
N
F
I
S
de
s
i
g
n
ba
s
e
d
on
p
r
e
d
i
c
t
i
on
m
ode
l
s
f
o
r
t
he
ph
ot
ovo
l
t
a
i
c
s
ys
t
e
m
,”
2
01
9
4
t
h
I
n
t
e
r
n
at
i
on
al
C
o
nf
e
r
e
nc
e
on
S
us
t
a
i
n
ab
l
e
I
n
f
or
m
a
t
i
o
n
E
n
gi
ne
e
r
i
ng
a
nd
T
e
c
hn
ol
og
y
,
2
01
9,
do
i
:
10
.1
109
/
S
I
E
T
4
80
54.
20
19.
89
861
33
.
[
24]
F
. M
. A
. H
a
di
,
H
. H
. A
l
y,
a
nd T
. L
i
t
t
l
e
, “
H
a
r
m
oni
c
s
f
or
e
c
a
s
t
i
ng of
w
i
nd
a
nd s
o
l
a
r
hybr
i
d m
ode
l
dr
i
ve
n by D
F
I
G
a
nd P
M
S
G
us
i
n
g
A
N
N
a
nd A
N
F
I
S
,”
I
E
E
E
A
c
c
e
s
s
, vol
. 11, pp. 55413
–
55424, 2023, doi
:
10.1109/
A
C
C
E
S
S
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[
25]
E
.
A
k
a
r
s
l
a
n
a
n
d F
. O
. H
oc
a
og
l
u
,
“
A
n
ove
l
s
ho
r
t
-
t
e
r
m
l
oa
d f
o
r
e
c
a
s
t
i
ng
a
p
pr
oa
c
h us
i
n
g
A
da
p
t
i
ve
ne
u
r
o
-
f
u
z
z
y
i
n
f
e
r
e
nc
e
s
ys
t
e
m
,
”
2
01
8
6t
h
I
nt
e
r
na
t
i
on
al
I
s
t
an
bu
l
Sm
ar
t
G
r
i
ds
an
d C
i
t
i
e
s
C
on
gr
e
s
s
a
nd
F
ai
r
,
pp.
1
60
–
16
3,
201
8,
do
i
:
1
0.1
10
9/
S
G
C
F
.2
01
8.8
40
896
4.
[
26]
A
.
A
z
e
e
m
,
I
.
I
s
m
a
i
l
,
S
.
M
.
J
a
m
e
e
l
,
a
nd
V
.
R
.
H
a
r
i
ndr
a
n,
“
E
l
e
c
t
r
i
c
a
l
l
oa
d
f
o
r
e
c
a
s
t
i
ng
m
ode
l
s
f
or
di
f
f
e
r
e
nt
ge
ne
r
a
t
i
on
m
oda
l
i
t
i
e
s
:
a
r
e
vi
e
w
,”
I
E
E
E
A
c
c
e
s
s
, vol
. 9, pp. 142239
–
142263, 2021, doi
:
10.1109/
A
C
C
E
S
S
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[
27]
H
. K
ha
n
, M
.
J
.
K
h
a
n,
a
n
d A
.
Q
a
y
yum
, “
N
e
u
r
a
l
ne
t
w
o
r
k
-
ba
s
e
d
l
oa
d
f
o
r
e
c
a
s
t
i
n
g m
ode
l
f
o
r
e
f
f
i
c
i
e
nt
c
ha
r
gi
n
g
of
e
l
e
c
t
r
i
c
ve
h
i
c
l
e
s
,”
20
22
7t
h
A
s
i
a
C
o
nf
e
r
e
nc
e
o
n
P
ow
e
r
a
nd
E
l
e
c
t
r
i
c
al
E
ng
i
ne
e
r
i
n
g,
pp
.
206
8
–
207
2,
20
22
,
doi
:
10.
11
09
/
A
C
P
E
E
539
04
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22
.97
83
828
.
[
28]
H
. W
a
ng
e
t
al
.
, “
E
l
e
c
t
r
i
c
v
e
hi
c
l
e
c
h
a
r
gi
ng l
oa
d c
l
u
s
t
e
r
i
ng a
nd l
oa
d
f
or
e
c
a
s
t
i
ng
ba
s
e
d on
l
ong s
hor
t
t
e
r
m
m
e
m
or
y ne
ur
a
l
ne
t
w
or
k,
”
2022 I
E
E
E
5t
h I
nt
e
r
nat
i
onal
E
l
e
c
t
r
i
c
al
and E
ne
r
gy
C
onf
e
r
e
nc
e
,
pp. 3196
–
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, 2022, doi
:
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C
I
E
E
C
54735.2022.9846570.
[
29]
A
.
A
.
N
a
s
s
a
r
,
K
.
G
a
ndhi
,
a
nd
W
.
G
.
M
or
s
i
,
“
E
l
e
c
t
r
i
c
ve
hi
c
l
e
s
l
oa
d
f
or
e
c
a
s
t
i
ng
c
ons
i
de
r
i
ng
t
he
e
f
f
e
c
t
of
C
O
V
I
D
-
19
pa
nde
m
i
c
,
”
2021 I
E
E
E
E
l
e
c
t
r
i
c
al
P
ow
e
r
and E
ne
r
gy
C
onf
e
r
e
nc
e
, E
P
E
C
2021
, pp. 440
–
444, 2021, doi
:
10.1109/
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P
E
C
52095.2021.9621740.
[
30]
P
.
A
l
m
a
l
e
c
k,
S
.
M
a
s
s
uc
c
o,
G
.
M
os
a
i
c
o,
M
.
S
a
vi
oz
z
i
,
P
.
S
e
r
r
a
,
a
nd
F
.
S
i
l
ve
s
t
r
o,
“
E
l
e
c
t
r
i
c
a
l
c
ons
um
pt
i
on
f
or
e
c
a
s
t
i
ng
i
n
s
por
t
s
ve
nue
s
:
a
pr
opos
e
d
a
ppr
oa
c
h
ba
s
e
d
on
ne
ur
a
l
ne
t
w
or
ks
a
nd
A
R
I
M
A
X
M
ode
l
s
,”
Sus
t
ai
nabl
e
C
i
t
i
e
s
and
Soc
i
e
t
y
,
vol
.
100,
2024,
doi
:
10.1016/
j
.s
c
s
.2023.105019.
[
31]
Al
-
K
how
a
r
i
z
m
i
,
S
.
E
f
e
ndi
,
M
.
K
.
M
.
N
a
s
ut
i
on,
a
nd
M
.
H
e
r
m
a
n,
“
T
he
r
ol
e
of
de
t
e
c
t
i
on
r
a
t
e
i
n
M
A
P
E
t
o
i
m
p
r
ove
m
e
a
s
ur
e
m
e
nt
a
c
c
ur
a
c
y
f
or
pr
e
di
c
t
i
ng
F
i
nT
e
c
h
da
t
a
i
n
va
r
i
ous
r
e
gr
e
s
s
i
on
s
,”
I
C
C
oSI
T
E
2023
-
I
nt
e
r
nat
i
onal
C
onf
e
r
e
nc
e
on
C
om
put
e
r
Sc
i
e
nc
e
,
I
nf
or
m
at
i
on
T
e
c
hnol
ogy
and
E
ngi
ne
e
r
i
ng:
D
i
gi
t
al
T
r
ans
f
o
r
m
at
i
on
St
r
at
e
gy
i
n
F
ac
i
ng
t
he
V
U
C
A
and
T
U
N
A
E
r
a
,
pp.
874
–
879
,
2023, doi
:
10.1109/
I
C
C
oS
I
T
E
57641.2023.10127820.
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32]
A
. R
.
L
ubi
s
,
S
. P
r
a
yuda
ni
, Y
. F
a
t
m
i
,
M
.
L
ubi
s
,
a
nd A
l
-
K
how
a
r
i
z
m
i
,
“
M
A
P
E
a
c
c
ur
a
c
y of
C
P
O
f
or
e
c
a
s
t
i
ng by
a
ppl
yi
ng f
uz
z
y t
i
m
e
s
e
r
i
e
s
,”
I
nt
e
r
nat
i
onal
C
onf
e
r
e
nc
e
on E
l
e
c
t
r
i
c
al
E
ngi
ne
e
r
i
ng, C
om
put
e
r
S
c
i
e
nc
e
and I
nf
or
m
at
i
c
s
(
E
E
C
SI
)
, pp. 370
–
373, 2021, doi
:
10.23919/
E
E
C
S
I
53397.2021.9624303.
[
33]
M
.
I
.
M
.
I
s
ha
m
,
H
.
N
.
H
j
H
a
r
on,
F
.
B
.
M
oha
m
e
d,
a
nd
C
.
V
.
S
i
a
ng,
“
V
R
w
e
l
d
i
ng
ki
t
:
a
c
c
ur
a
c
y
c
om
pa
r
i
s
on
be
t
w
e
e
n
s
m
a
r
t
phon
e
V
R
a
nd
s
t
a
nda
l
one
V
R
us
i
ng
R
M
S
E
,”
2021
I
E
E
E
I
nt
e
r
nat
i
onal
C
onf
e
r
e
nc
e
on
C
om
put
i
ng,
I
C
O
C
O
2021
,
pp.
341
–
346,
2021,
doi
:
10.1109/
I
C
O
C
O
53166.2021.9673577.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
. 14, No. 3, J
une
20
25
:
1790
-
1798
1798
B
I
O
G
R
A
P
H
I
E
S
O
F
A
U
T
H
O
R
S
Yoga
Tri
Nugraha
received
his
master
degree
in
electrical
e
ngineering
from
Universitas
Muhammadiyah
Sumatera
Utara
(UMSU),
Indonesia
in
2019.
He
is
currently
a
researcher
in
Department
of
Electrical
Engineering,
Universitas
Al
-
A
zhar
Medan.
His
research
interest
includes
renewa
ble
energy,
internet
of
things,
com
munication
engineer
ing,
mechatron
ics,
artificia
l
intelligence
and
power
system.
He
can
be
contacted
at
email:
yogatrinugraha16@gmail.com
.
Catra
Indra
Cahyadi
completed
a
bachelor
of
Applied
Science
degree
in
Airport
Electrical
Engineering
in
2004,
and
a
masters
in
Electrical
Engine
ering
in
2024.
Currently
carrying
out
research
in
the
fields
of
aviation
engineerin
g,
airpo
rt
electrical
engineerin
g,
transmission
and
distribution,
and
control
systems.
He
can
be
contacte
d
at
email:
catraindracahy
adi@
gmail.co
m.
Rizkha
Rida
received
his
masters
degree
in
Industrial
Engineering from
University
of
Sumatera
Utara
in
2021.
She
is
currently
a
researcher
in
Department
of
Industrial
Engineering,
Universitas
Al
-
Azhar
Medan.
Her
research
interest
includes
supply
chain,
manufactu
ring,
product
design
and
manageme
nt
engineer
ing.
She
can
be
contacted
at
email:
rizkharida26@
gmail.com
.
Margie
Subahagia
Ningsih
received
her
master
degree
in
indust
rial
engineering
from Universi
tas Sumat
era Utara, Indonesi
a in
2013. She is currently a
researcher
in Depar
tment
of
Industrial
Engineering,
Universitas
Al
-
Azhar.
Her
research
interest
includes
industrial
engineerin
g.
She ca
n be c
ontact
ed at
email:
margiesuba
hagia@rocketmail.com
.
Dewi
Sholeha
received
her
master
degree
in
Electrical
E
ngineering
from
Universitas
Muhammadiyah
Sumatera
Utara
(UMSU),
Indonesia
in
2022.
She
is
currently
a
researcher
in
Department
of
Electrical
Engineering,
Universitas
Da
rma
Agung.
Her
research
interest
includes
renewa
ble
energy,
communication
engineer
ing
and
power
system.
She
can
be
contacted
at email
:
alkhansadew
i@
gmail.co
m
.
Indra
Roza
received
his
master’s
degree
in
Electric
al
Engineeri
ng
from
Institut
Sains
dan
Teknologi
Nasional
(ISTN),
Indonesia
in
2011.
He
is
c
urrently
a
researcher
and
lecturer
in
Departme
nt
of
Electrica
l
Engineerin
g,
Universitas
Harapa
n
Medan.
His
resear
ch
interest
includes
electric
al
engineer
ing,
power
quality,
protection
syst
em,
grounding
system
an
d
power system.
He can be contacted at email:
indraroz
a.ir@gmail.com.
Evaluation Warning : The document was created with Spire.PDF for Python.