I
nte
rna
t
io
na
l J
o
urna
l o
f
E
lect
rica
l a
nd
Co
m
p
ute
r
E
ng
in
ee
ring
(
I
J
E
CE
)
Vo
l.
11
,
No
.
4
,
A
u
g
u
s
t
2021
,
p
p
.
3
5
5
9
~
3
5
6
6
I
SS
N:
2
0
8
8
-
8708
,
DOI
: 1
0
.
1
1
5
9
1
/
i
j
ec
e
.
v
1
1
i
4
.
pp
3
5
5
9
-
3
5
6
6
3559
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ec
e.
ia
esco
r
e.
co
m
T
w
o
-
step artific
ia
l neural ne
tw
o
rk
to esti
m
a
te
t
he
so
la
r
ra
dia
tion a
t
J
a
v
a
Isla
nd
Adi K
urnia
w
a
n
1
,
E
ij
i Shi
nta
ku
2
1
De
p
a
rtme
n
t
o
f
M
a
rin
e
En
g
in
e
e
ri
n
g
,
In
stit
u
t
T
e
k
n
o
lo
g
i
S
e
p
u
l
u
h
No
p
e
m
b
e
r,
In
d
o
n
e
sia
2
De
p
a
rtme
n
t
o
f
T
ra
n
sp
o
rtatio
n
a
n
d
En
v
ir
o
n
m
e
n
tal
S
y
ste
m
s,
Hiro
sh
im
a
Un
iv
e
rsit
y
,
Ja
p
a
n
Art
icle
I
nfo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Sep
3
,
2
0
2
0
R
ev
i
s
ed
J
an
1
3
,
2
0
2
1
A
cc
ep
ted
Feb
1
0
,
2
0
2
1
T
h
e
a
v
a
il
a
b
il
it
y
o
f
in
f
o
r
m
a
ti
o
n
a
b
o
u
t
so
lar
ra
d
iati
o
n
c
h
a
r
a
c
teristics
,
p
a
rti
c
u
larly
so
lar
ra
d
iatio
n
p
re
d
ictio
n
s,
is
im
p
o
rtan
t
f
o
r
e
ff
i
c
ien
tl
y
d
e
sig
n
in
g
so
lar
e
n
e
rg
y
s
y
ste
m
s.
S
o
lar
r
a
d
iatio
n
i
n
f
o
rm
a
ti
o
n
is
n
o
t
a
v
a
il
a
b
le
in
In
d
o
n
e
sia
b
e
c
a
u
se
o
f
f
icia
l
m
e
a
s
u
re
m
e
n
ts
h
a
v
e
n
o
t
b
e
e
n
c
o
n
d
u
c
ted
b
y
th
e
I
n
d
o
n
e
sia
n
M
e
teo
r
o
lo
g
ica
l,
Cli
m
a
to
lo
g
y
,
a
n
d
G
e
o
p
h
y
sic
a
l
Ag
e
n
c
y
(BM
KG
).
In
th
is
stu
d
y
,
a
n
e
w
t
w
o
-
ste
p
a
rti
f
icia
l
n
e
u
ra
l
n
e
t
w
o
rk
(
AN
N)
is
p
ro
p
o
se
d
to
e
sti
m
a
te
b
o
th
th
e
d
a
il
y
a
v
e
ra
g
e
a
n
d
h
o
u
rly
so
lar
ra
d
iatio
n
a
t
Ja
v
a
Isla
n
d
,
In
d
o
n
e
sia
.
T
h
e
in
p
u
t
p
a
ra
m
e
te
rs
f
o
r
th
e
d
a
il
y
a
v
e
ra
g
e
so
lar
ra
d
iatio
n
e
sti
m
a
ti
o
n
a
re
th
e
lo
c
a
ti
o
n
a
n
d
ti
m
e
re
q
u
ired
,
a
l
o
n
g
w
it
h
f
iv
e
se
lec
ted
m
o
n
th
ly
m
e
teo
ro
lo
g
ica
l
p
a
ra
m
e
t
e
rs
th
a
t
BM
KG
p
re
d
icts
f
o
r
th
e
su
b
se
q
u
e
n
t
m
o
n
th
.
T
h
e
se
le
c
ted
m
e
t
e
o
ro
lo
g
ica
l
p
a
ra
m
e
ter
s
a
r
e
te
m
p
e
r
a
tu
re
s,
re
lativ
e
hum
id
it
y
,
a
n
d
p
re
c
ip
it
a
ti
o
n
.
T
h
e
e
stim
a
ted
d
a
il
y
a
v
e
ra
g
e
so
lar
r
a
d
iatio
n
is
th
e
n
u
se
d
a
s
th
e
i
n
p
u
t
p
a
ra
m
e
t
e
r
o
f
th
e
h
o
u
rly
so
lar
ra
d
iatio
n
e
stim
a
ti
o
n
a
lo
n
g
w
it
h
th
e
lo
c
a
l
ti
m
e
a
n
d
l
o
c
a
ti
o
n
.
T
h
e
A
NN
train
in
g
wa
s
c
o
n
d
u
c
te
d
u
sin
g
tw
o
y
e
a
rs
o
f
d
a
ta,
2
0
1
8
a
n
d
2
0
1
9
,
f
ro
m
S
u
ra
b
a
y
a
a
n
d
Ja
k
a
rta,
w
h
il
e
th
e
v
a
li
d
a
ti
o
n
w
a
s
p
e
rf
o
r
m
e
d
in
th
e
sa
m
e
c
it
ies
f
o
r
Ja
n
u
a
r
y
th
ro
u
g
h
J
u
ly
2
0
2
0
.
T
h
e
a
c
c
u
ra
c
y
o
f
th
e
p
ro
p
o
se
d
m
e
th
o
d
is
c
o
m
p
a
ra
b
le
to
p
re
v
io
u
s
stu
d
ies
w
it
h
a
n
a
v
e
ra
g
e
R2
o
f
9
8
.
7
0
%
f
o
r
th
e
d
a
il
y
a
v
e
ra
g
e
so
lar
ra
d
iatio
n
e
sti
m
a
te an
d
9
7
.
4
4
%
f
o
r
th
e
h
o
u
rl
y
so
lar rad
iatio
n
e
stim
a
te.
K
ey
w
o
r
d
s
:
Dail
y
a
v
er
ag
e
s
o
lar
r
ad
iatio
n
E
n
er
g
y
f
o
r
ec
asti
n
g
Glo
b
al
s
o
lar
r
ad
iatio
n
Ho
u
r
l
y
s
o
lar
r
ad
iatio
n
Mu
ltil
a
y
er
f
ee
d
-
f
o
r
w
ar
d
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
:
A
d
i K
u
r
n
ia
w
a
n
Dep
ar
t
m
en
t o
f
Ma
r
in
e
E
n
g
i
n
e
er
in
g
I
n
s
tit
u
t T
ek
n
o
lo
g
i Sep
u
l
u
h
No
p
em
b
er
I
T
S
Stre
et
,
Kep
u
tih
,
Su
k
o
lilo
,
Su
r
ab
a
y
a
6
0
1
1
1
,
I
n
d
o
n
esia
E
m
ail:
ad
i.k
u
r
n
ia
w
an
@
n
e.
its
.
ac
.
id
1.
I
NT
RO
D
UCT
I
O
N
As
o
f
No
v
e
m
b
er
2
0
1
9
,
I
n
d
o
n
esia
h
as
u
tili
ze
d
o
n
l
y
1
5
2
MW
o
r
0
.
0
2
8
%
o
f
its
ab
u
n
d
an
t
5
3
6
GW
s
o
lar
en
er
g
y
p
o
ten
tial
t
h
r
o
u
g
h
s
o
lar
en
er
g
y
s
y
s
te
m
s
[
1
]
.
A
lack
o
f
o
f
f
ic
ial
s
o
lar
r
ad
iatio
n
m
ea
s
u
r
e
m
en
t
s
co
u
ld
b
e
o
n
e
o
f
th
e
f
ac
to
r
s
co
n
tr
ib
u
ti
n
g
to
t
h
e
s
lo
w
d
e
v
elo
p
m
e
n
t
o
f
s
o
lar
en
er
g
y
s
y
s
te
m
s
,
a
s
o
p
ti
m
al
d
esi
g
n
in
g
b
ec
o
m
e
s
m
o
r
e
d
if
f
ic
u
lt
w
i
th
o
u
t
th
is
i
n
f
o
r
m
atio
n
[
2
]
.
T
h
i
s
p
r
o
b
lem
co
u
ld
b
e
o
v
er
co
m
e
b
y
g
e
n
er
ati
n
g
a
n
ac
cu
r
ate
s
o
lar
r
ad
iatio
n
esti
m
a
to
r
f
o
r
a
s
p
ec
if
ic
lo
ca
tio
n
.
E
s
ti
m
a
tes
o
f
s
o
lar
r
ad
iatio
n
h
a
v
e
b
ee
n
u
s
ed
i
n
v
ar
io
u
s
o
p
ti
m
al
s
o
lar
e
n
er
g
y
d
es
ig
n
.
T
h
e
a
n
n
u
al
s
o
lar
r
ad
iatio
n
ca
lcu
latio
n
h
as
b
ee
n
u
s
ed
to
d
eter
m
in
e
t
h
e
id
ea
l
lo
ca
tio
n
to
b
u
ild
a
p
h
o
to
v
o
ltaic
s
y
s
te
m
[
3
,
4
]
.
T
h
e
m
o
n
t
h
l
y
to
tal,
o
r
d
ail
y
av
er
a
g
e,
s
o
lar
r
ad
ia
tio
n
is
r
eq
u
ir
ed
f
o
r
th
e
o
p
ti
m
a
l
s
izin
g
o
f
s
o
la
r
p
an
els
o
r
s
to
r
ag
e
s
y
s
te
m
s
[
5
-
7
]
,
w
h
ile
d
eter
m
in
i
n
g
p
a
n
el
in
s
tallatio
n
an
g
le
s
ca
lls
f
o
r
th
e
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
[
8
]
.
Var
io
u
s
m
et
h
o
d
s
h
av
e
b
ee
n
p
r
o
p
o
s
ed
to
esti
m
ate
eit
h
er
t
h
e
d
ail
y
a
v
er
a
g
e
o
r
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
.
T
h
e
ar
tif
icial
n
eu
r
al
n
et
w
o
r
k
(
A
N
N)
m
et
h
o
d
f
o
r
esti
m
at
io
n
is
o
n
e
o
f
th
e
m
o
s
t
p
o
p
u
lar
m
e
th
o
d
s
f
o
r
t
h
e
d
ail
y
av
er
ag
e
p
r
ed
ictio
n
d
u
e
to
it
s
h
ig
h
ac
cu
r
ac
y
[
9
,
1
0
]
.
W
h
ile
a
w
id
er
r
an
g
e
o
f
m
et
h
o
d
s
h
a
s
b
e
en
u
s
ed
to
es
ti
m
ate
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
11
,
No
.
4
,
A
u
g
u
s
t 2
0
2
1
:
3
5
5
9
-
3566
3560
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
,
ANN
-
b
ased
m
e
th
o
d
s
h
av
e
al
s
o
b
ee
n
ap
p
lied
w
it
h
ac
cu
r
ate
r
es
u
l
ts
.
T
h
o
s
e
m
eth
o
d
s
in
cl
u
d
e
m
u
l
tila
y
er
p
er
ce
p
tr
o
n
[
1
1
]
,
d
ee
p
lea
r
n
in
g
[
1
2
]
,
ad
a
p
tiv
e
n
eu
r
o
-
f
u
zz
y
[
1
3
,
1
4
]
,
J
o
r
d
an
r
ec
u
r
r
en
t
[
1
5
]
an
d
co
m
p
ar
is
o
n
o
f
v
ar
io
u
s
m
et
h
o
d
s
[
1
6
]
.
Ho
w
e
v
er
,
th
o
s
e
a
f
o
r
e
m
en
tio
n
ed
m
et
h
o
d
s
ca
n
n
o
t
b
e
u
s
ed
f
o
r
esti
m
ati
n
g
s
o
lar
r
ad
iatio
n
in
I
n
d
o
n
esia
b
ec
au
s
e
t
h
e
y
r
eq
u
i
r
e
m
eteo
r
o
lo
g
ical
in
p
u
t
p
ar
am
eter
s
t
h
at
ar
e
n
o
t
m
ea
s
u
r
ed
b
y
I
n
d
o
n
e
s
ian
Me
t
eo
r
o
lo
g
ical,
C
li
m
a
to
lo
g
y
,
a
n
d
Geo
p
h
y
s
ica
l
A
g
e
n
c
y
(
B
MK
G)
.
T
h
e
u
n
av
ai
lab
le
in
p
u
t p
ar
a
m
e
ter
s
ar
e
h
o
u
r
l
y
cl
o
u
d
co
v
er
,
clea
r
n
ess
i
n
d
ex
,
at
m
o
s
p
h
er
ic
p
r
ess
u
r
e,
an
d
v
i
s
ib
i
lit
y
.
T
h
e
o
b
j
ec
tiv
e
o
f
th
i
s
s
t
u
d
y
is
to
b
u
ild
a
s
o
lar
r
ad
iatio
n
esti
m
ato
r
u
s
in
g
a
n
A
NN
-
b
ased
m
et
h
o
d
an
d
th
e
m
eteo
r
o
lo
g
ical
d
ata
t
y
p
es
av
ailab
le
in
I
n
d
o
n
esia.
B
ec
au
s
e
n
o
h
o
u
r
l
y
w
ea
t
h
er
in
f
o
r
m
ati
o
n
is
av
ai
lab
le,
th
e
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
esti
m
at
o
r
r
elies
o
n
t
h
e
d
ail
y
a
v
er
ag
e
s
o
lar
r
ad
iatio
n
i
n
t
h
e
s
a
m
e
m
o
n
t
h
.
T
h
er
ef
o
r
e,
a
t
w
o
-
s
tep
ANN
i
s
r
eq
u
ir
ed
.
T
h
e
f
ir
s
t
ANN
(
A
NN
-
1
)
p
r
ed
icts
t
h
e
d
ail
y
av
er
a
g
e
s
o
lar
r
ad
iatio
n
u
s
i
n
g
th
e
s
elec
ted
m
o
n
t
h
l
y
w
ea
t
h
er
p
ar
a
m
eter
s
,
w
h
ile
t
h
e
s
ec
o
n
d
ANN
(
A
NN
-
2
)
p
r
ed
icts
th
e
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
u
s
i
n
g
t
h
e
o
u
tp
u
t
o
f
A
NN
-
1
.
B
o
th
th
e
tr
ai
n
in
g
an
d
th
e
v
al
id
atio
n
o
f
t
h
e
ANNs
w
er
e
p
e
r
f
o
r
m
ed
u
s
i
n
g
d
ata
f
r
o
m
t
h
e
c
ities
o
f
J
ak
ar
ta
an
d
Su
r
ab
a
y
a,
w
h
ich
ar
e
lo
ca
ted
o
n
J
av
a
I
s
la
n
d
.
T
h
e
citie
s
w
er
e
s
elec
ted
b
ec
au
s
e
th
e
y
h
av
e
th
e
lar
g
e
s
t
elec
tr
ici
t
y
d
e
m
an
d
in
I
n
d
o
n
es
ia.
T
h
e
r
esu
lt
s
o
f
t
h
is
r
esear
ch
ca
n
b
e
u
s
e
d
t
o
h
e
l
p
s
o
l
a
r
e
n
e
r
g
y
s
y
s
t
e
m
d
e
s
i
g
n
e
r
s
t
o
b
u
i
l
d
h
i
g
h
-
e
f
f
i
c
i
e
n
c
y
p
h
o
t
o
v
o
l
t
a
i
c
s
y
s
t
e
m
s
i
n
I
n
d
o
n
e
s
i
a
,
e
s
p
e
c
i
a
l
l
y
o
n
J
av
a
I
s
la
n
d
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
I
n
th
i
s
s
t
u
d
y
,
a
t
w
o
-
s
tep
A
N
N
is
p
r
o
p
o
s
ed
t
o
esti
m
ate
th
e
a
m
o
u
n
t
o
f
s
o
lar
r
ad
iatio
n
at
J
av
a
I
s
lan
d
.
A
N
N
-
1
es
ti
m
ates
t
h
e
a
m
o
u
n
t
o
f
th
e
d
ail
y
a
v
er
ag
e
s
o
lar
r
ad
iatio
n
,
w
h
ich
i
s
t
h
en
u
s
ed
b
y
A
N
N
-
2
to
est
i
m
a
te
th
e
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
in
t
h
e
s
a
m
e
m
o
n
t
h
.
T
h
e
co
n
f
ig
u
r
at
io
n
o
f
t
h
e
t
w
o
-
s
tep
A
NN
is
d
e
p
icted
in
Fig
u
r
e
1
.
T
h
e
m
eteo
r
o
lo
g
ical
d
ata
f
o
r
tr
ain
i
n
g
b
o
th
n
et
w
o
r
k
s
w
er
e
f
r
o
m
2
0
1
8
an
d
2
0
1
9
f
r
o
m
th
e
cit
y
o
f
J
ak
ar
ta,
w
h
ic
h
is
lo
ca
ted
in
t
h
e
w
ester
n
p
ar
t
o
f
J
av
a
I
s
lan
d
,
a
n
d
Su
r
ab
a
y
a,
w
h
ic
h
is
t
h
e
ca
p
ital
o
f
E
a
s
t
J
av
a
p
r
o
v
in
ce
.
T
h
e
A
N
Ns
w
er
e
b
u
i
lt
i
n
M
A
T
L
AB
en
v
ir
o
n
m
e
n
t
u
s
i
n
g
n
e
u
r
al
n
et
w
o
r
k
to
o
lb
o
x
.
T
h
e
s
elec
tio
n
o
f
th
e
i
n
p
u
t
an
d
t
h
e
n
u
m
b
er
o
f
h
id
d
en
n
e
u
r
o
n
s
ar
e
ex
p
lain
ed
i
n
t
h
e
s
u
b
-
s
ec
tio
n
s
.
T
o
g
et
t
h
e
esti
m
at
io
n
r
es
u
lt,
t
h
e
A
NN
m
o
d
el
w
a
s
ad
d
ed
to
t
h
e
Si
m
u
li
n
k
a
n
d
w
as
e
x
ec
u
ted
w
it
h
th
e
m
eteo
r
o
lo
g
ical
d
ata
o
f
S
u
r
ab
ay
a
an
d
J
ak
ar
ta
f
o
r
J
an
u
ar
y
t
h
r
o
u
g
h
J
u
l
y
2
0
2
0
a
s
th
e
in
p
u
t.
T
h
e
v
alid
atio
n
o
f
th
e
ac
cu
r
ac
y
o
f
th
e
m
o
d
el
w
a
s
p
er
f
o
r
m
ed
b
y
co
m
p
ar
i
n
g
t
h
e
est
i
m
a
tio
n
r
es
u
lts
w
it
h
th
e
m
ea
s
u
r
ed
s
o
lar
r
ad
iatio
n
in
t
h
e
s
a
m
e
p
er
io
d
.
Fig
u
r
e
1
.
C
o
n
f
ig
u
r
atio
n
o
f
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
2
.
1
.
ANN
-
1
d
esig
n
A
N
N
-
1
e
s
ti
m
ate
s
t
h
e
d
ail
y
a
v
er
ag
e
s
o
lar
r
ad
iatio
n
b
y
u
s
i
n
g
t
h
e
i
n
p
u
t
s
o
f
m
o
n
t
h
,
g
eo
g
r
ap
h
ical
p
o
s
itio
n
,
an
d
m
eteo
r
o
lo
g
ical
d
ata
o
f
d
aily
av
er
a
g
e
m
i
n
i
m
u
m
,
m
a
x
i
m
u
m
,
an
d
av
er
a
g
e
tem
p
er
at
u
r
e,
r
elativ
e
h
u
m
id
it
y
,
an
d
p
r
ec
ip
itatio
n
.
T
h
ese
m
e
teo
r
o
lo
g
ical
d
ata
w
er
e
s
elec
ted
b
ec
au
s
e
B
MK
G
f
o
r
e
ca
s
ts
th
e
s
e
d
ata
f
o
r
th
e
s
u
b
s
eq
u
e
n
t
m
o
n
t
h
.
T
h
u
s
,
u
s
i
n
g
th
e
s
e
m
eteo
r
o
lo
g
ical
d
a
ta
allo
w
s
f
o
r
th
e
es
ti
m
atio
n
o
f
th
e
d
ail
y
av
er
a
g
e
s
o
lar
r
ad
iatio
n
f
o
r
th
e
f
o
llo
w
i
n
g
m
o
n
t
h
.
T
h
e
g
eo
g
r
ap
h
ical
p
o
s
itio
n
s
o
f
lat
itu
d
e
a
n
d
lo
n
g
i
tu
d
e
w
er
e
i
n
c
l
u
d
ed
b
ec
au
s
e
th
e
p
o
s
itio
n
o
f
t
h
e
s
u
n
,
an
d
th
u
s
th
e
s
o
lar
r
ad
iatio
n
,
v
ar
ies
f
o
r
d
if
f
er
e
n
t
lo
ca
tio
n
s
in
th
e
s
a
m
e
m
o
n
t
h
.
T
h
e
d
ail
y
s
o
lar
r
ad
iatio
n
d
ata
f
o
r
tr
ai
n
in
g
ANN
-
1
w
as
tak
e
n
f
r
o
m
t
h
e
N
A
S
A
p
o
w
er
d
ata
b
ase.
T
h
e
d
ata
w
a
s
co
n
v
er
ted
in
to
th
e
d
ail
y
a
v
er
ag
e
s
o
lar
r
ad
iatio
n
,
w
it
h
ea
ch
d
ay
i
n
a
d
ef
in
ed
m
o
n
th
a
s
s
u
m
ed
to
h
av
e
eq
u
al
s
o
lar
r
ad
iatio
n
.
Deta
iled
in
f
o
r
m
atio
n
ab
o
u
t t
h
e
i
n
p
u
t
-
o
u
tp
u
t
p
ar
am
eter
s
is
p
r
esen
ted
i
n
T
ab
le
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:
2
0
8
8
-
8708
Tw
o
-
s
tep
a
r
tifi
cia
l n
eu
r
a
l n
etw
o
r
k
to
esti
ma
te
th
e
s
o
la
r
r
a
d
ia
tio
n
a
t J
a
v
a
I
s
la
n
d
(
A
d
i Ku
r
n
ia
w
a
n
)
3561
T
ab
le
1
.
P
ar
am
eter
s
o
f
ANN
-
1
Pa
r
a
me
t
e
r
N
o
t
a
t
i
o
n
U
n
i
t
M
i
n
.
M
a
x
.
A
v
e
.
L
a
t
i
t
u
d
e
φ
°
-
7
.
2
5
-
6
.
2
1
-
6
.
7
3
L
o
n
g
i
t
u
d
e
ρ
°
1
0
6
.
8
5
1
1
2
.
7
5
1
0
9
.
8
M
o
n
t
h
n
u
m
b
e
r
n
1
12
6
.
5
M
i
n
i
m
u
m
t
e
mp
e
r
a
t
u
r
e
T
n
°C
2
3
.
0
5
2
7
.
4
2
6
.
2
3
M
a
x
i
m
u
m
t
e
mp
e
r
a
t
u
r
e
T
x
°C
3
0
.
3
6
3
6
.
3
7
3
3
.
1
A
v
e
r
a
g
e
t
e
mp
e
r
a
t
u
r
e
T
a
°C
2
7
.
5
3
3
1
.
3
8
2
8
.
8
3
R
e
l
a
t
i
v
e
h
u
mi
d
i
t
y
R
H
%
6
1
.
5
4
8
2
.
4
3
7
3
.
8
P
r
e
c
i
p
i
t
a
t
i
o
n
R
R
mm
0
2
1
.
5
2
5
.
2
9
D
a
i
l
y
a
v
e
r
a
g
e
r
a
d
i
a
t
i
o
n
G
m
k
W
h
/
m
2
4
.
0
9
6
.
7
9
6
.
1
6
T
h
e
n
u
m
b
er
o
f
h
id
d
en
n
e
u
r
o
n
s
in
A
NN
-
1
w
a
s
ch
o
s
en
b
y
co
m
p
ar
i
n
g
t
h
e
r
eg
r
e
s
s
io
n
v
a
lu
e
(
R
)
d
u
r
in
g
tr
ain
i
n
g
f
o
r
v
ar
io
u
s
n
u
m
b
er
s
o
f
n
e
u
r
o
n
s
i
n
t
h
e
h
id
d
en
la
y
e
r
.
T
h
e
ca
n
d
id
ates
f
o
r
t
h
e
n
u
m
b
er
o
f
th
e
h
id
d
en
n
eu
r
o
n
s
ar
e
d
eter
m
in
ed
b
y
t
h
e
r
u
les [
1
7
]
:
ℎ
≥
2
3
+
(
1
)
ℎ
<
2
(
2
)
w
h
er
e
h
is
th
e
n
u
m
b
er
o
f
th
e
h
id
d
en
n
eu
r
o
n
s
,
i
is
t
h
e
n
u
m
b
er
o
f
th
e
i
n
p
u
ts
,
a
n
d
o
is
th
e
n
u
m
b
er
o
f
t
h
e
o
u
tp
u
ts
.
W
ith
ei
g
h
t
i
n
p
u
ts
an
d
o
n
e
o
u
t
p
u
t,
t
h
e
n
u
m
b
er
o
f
h
id
d
en
n
e
u
r
o
n
s
i
s
b
et
w
ee
n
s
ix
a
n
d
1
5
.
ANN
-
1
w
a
s
tr
ain
ed
ten
ti
m
e
s
f
o
r
ea
ch
n
u
m
b
er
o
f
h
id
d
en
n
e
u
r
o
n
s
.
T
h
e
co
m
p
ar
is
o
n
o
f
t
h
e
h
ig
h
es
t
R
f
o
r
ea
ch
n
u
m
b
er
o
f
h
id
d
en
n
e
u
r
o
n
s
is
s
h
o
w
n
i
n
Fi
g
u
r
e
2
.
A
cc
o
r
d
in
g
to
t
h
i
s
an
al
y
s
i
s
,
th
e
p
r
ef
er
r
ed
n
u
m
b
er
o
f
h
id
d
en
n
e
u
r
o
n
s
f
o
r
A
N
N
-
1
i
s
1
5
.
T
h
e
tr
ain
in
g
r
e
g
r
ess
io
n
li
n
e
o
f
th
e
p
r
e
f
er
r
ed
A
N
N
s
tr
u
ct
u
r
e
is
s
h
o
w
n
i
n
Fig
u
r
e
3
.
T
h
e
f
e
e
d
-
f
o
r
w
a
r
d
L
e
v
e
n
b
e
r
g
-
M
a
r
q
u
a
r
d
t
m
e
t
h
o
d
w
a
s
c
h
o
s
e
n
t
o
t
r
a
i
n
A
N
N
-
1
d
u
e
t
o
i
t
s
s
p
e
e
d
a
n
d
s
t
a
b
l
e
c
o
n
v
e
r
g
e
n
c
e
[
1
8
]
.
T
h
e
i
t
e
r
a
t
i
o
n
-
s
t
o
p
p
i
n
g
c
r
i
t
e
r
i
a
w
e
r
e
b
a
s
e
d
o
n
t
h
e
m
i
n
i
m
u
m
m
e
a
n
s
q
u
a
r
e
d
e
r
r
o
r
(
M
S
E
)
,
w
h
i
c
h
i
s
c
a
l
c
u
l
a
t
e
d
a
s
(
3
)
.
2
2
11
11
MS
E
nn
k
k
k
kk
e
t
y
nn
(
3
)
w
h
er
e
n
is
th
e
to
tal
n
u
m
b
er
o
f
s
a
m
p
le
s
o
f
th
e
o
u
tp
u
t
p
ar
a
m
e
ter
,
k
is
t
h
e
i
n
d
ex
o
f
t
h
e
o
u
tp
u
t
s
a
m
p
le
s
,
e
i
s
t
h
e
er
r
o
r
o
f
th
e
o
u
tp
u
t,
t
is
t
h
e
tar
g
et
v
al
u
e
o
f
t
h
e
o
u
tp
u
t
f
r
o
m
t
h
e
d
ata,
a
n
d
y
i
s
t
h
e
o
u
tp
u
t
v
alu
e
o
b
tain
ed
f
r
o
m
th
e
ca
lcu
lati
o
n
o
f
t
h
e
A
N
N
.
Fig
u
r
e
2
.
C
o
m
p
ar
is
o
n
o
f
r
e
g
r
ess
io
n
v
al
u
es
f
o
r
A
N
N
-
1
Fig
u
r
e
3
.
R
eg
r
es
s
io
n
li
n
e
f
o
r
A
N
N
-
1
tr
ai
n
in
g
2
.
2
.
ANN
-
2
des
ig
n
A
N
N
-
2
esti
m
ate
s
h
o
u
r
l
y
s
o
la
r
r
ad
iatio
n
b
ased
o
n
th
e
d
aily
a
v
er
ag
e
s
o
lar
r
ad
iatio
n
,
g
e
o
g
r
ap
h
ical
p
o
s
itio
n
,
m
o
n
t
h
,
an
d
lo
ca
l
h
o
u
r
.
T
h
e
ad
v
an
ta
g
e
o
f
th
i
s
m
et
h
o
d
is
t
h
at
it
d
o
es
n
o
t
r
eq
u
ir
e
an
y
h
o
u
r
l
y
w
ea
t
h
er
p
ar
am
eter
s
as
in
p
u
t,
w
h
ich
ar
e
n
o
t
m
ea
s
u
r
ed
an
d
r
ec
o
r
d
ed
b
y
B
MK
G.
T
h
e
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
d
ata
f
o
r
t
h
e
A
N
N
-
2
tr
ai
n
i
n
g
w
as
ta
k
e
n
f
r
o
m
th
e
co
m
m
er
cial
So
lcast
w
eb
s
i
te
f
o
r
t
h
e
cit
ies
o
f
J
ak
a
r
ta
an
d
S
u
r
ab
a
y
a
i
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
11
,
No
.
4
,
A
u
g
u
s
t 2
0
2
1
:
3
5
5
9
-
3566
3562
2
0
1
8
an
d
2
0
1
9
.
T
h
e
r
a
w
d
at
a
w
er
e
co
n
v
er
ted
i
n
to
t
h
e
a
v
er
ag
e
o
f
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
in
ea
ch
m
o
n
t
h
.
Deta
iled
in
f
o
r
m
atio
n
ab
o
u
t th
e
in
p
u
t
-
o
u
tp
u
t p
ar
a
m
eter
s
i
s
li
s
ted
in
T
ab
le
2
.
T
ab
le
2
.
P
ar
am
eter
s
o
f
ANN
-
2
P
a
r
a
me
t
e
r
N
o
t
a
t
i
o
n
U
n
i
t
M
i
n
.
M
a
x
.
A
v
e
.
L
o
c
a
l
t
i
me
h
o
u
r
t
h
5
18
1
1
.
5
H
o
u
r
l
y
so
l
a
r
r
a
d
i
a
t
i
o
n
G
h
W
h
/
m
2
0
9
9
8
.
0
3
3
9
1
.
9
Usi
n
g
t
h
e
s
a
m
e
m
et
h
o
d
as
d
escr
ib
ed
in
s
ec
tio
n
2
.
1
,
th
e
n
u
m
b
er
o
f
h
id
d
en
n
e
u
r
o
n
s
f
o
r
A
N
N
-
2
w
a
s
also
d
eter
m
i
n
ed
b
y
co
m
p
ar
in
g
R
v
al
u
es
f
o
r
ca
n
d
id
ates
d
eter
m
i
n
ed
u
s
i
n
g
(
1
)
an
d
(
2
)
.
T
h
e
r
an
g
e
o
f
th
e
n
u
m
b
er
o
f
h
id
d
en
n
e
u
r
o
n
s
w
a
s
b
et
w
ee
n
f
o
u
r
an
d
n
i
n
e,
an
d
n
in
e
w
as
s
elec
ted
as
t
h
e
n
u
m
b
er
o
f
h
id
d
en
n
e
u
r
o
n
s
d
u
e
to
h
av
i
n
g
t
h
e
h
i
g
h
est
R
,
as
s
h
o
w
n
i
n
Fi
g
u
r
e
4
.
T
h
e
r
e
g
r
ess
io
n
lin
e
d
u
r
in
g
th
e
A
NN
-
2
tr
ai
n
i
n
g
w
i
th
n
in
e
h
id
d
e
n
n
eu
r
o
n
s
is
d
ep
icted
in
Fi
g
u
r
e
5
.
Fig
u
r
e
4
.
C
o
m
p
ar
is
o
n
o
f
r
e
g
r
ess
io
n
v
al
u
es
f
o
r
A
N
N
-
2
Fig
u
r
e
5.
R
eg
r
es
s
io
n
li
n
e
f
o
r
A
N
N
-
2
tr
ai
n
in
g
3.
RE
SU
L
T
S
A
ND
D
I
SCU
SS
I
O
N
Valid
atio
n
o
f
t
h
e
p
r
o
p
o
s
ed
m
eth
o
d
w
a
s
co
m
p
leted
b
y
co
m
p
ar
in
g
t
h
e
esti
m
ated
r
esu
lts
f
r
o
m
ea
c
h
A
N
N
w
ith
t
h
e
m
ea
s
u
r
ed
s
o
lar
r
ad
iatio
n
in
J
ak
ar
ta
an
d
Su
r
a
b
ay
a
f
o
r
J
an
u
ar
y
t
h
r
o
u
g
h
J
u
l
y
2
0
2
0
.
A
lth
o
u
g
h
th
e
co
m
p
ar
is
o
n
w
a
s
n
o
t
p
er
f
o
r
m
ed
f
o
r
a
f
u
ll
y
ea
r
,
t
h
e
s
e
lect
ed
m
o
n
t
h
s
i
n
cl
u
d
e
p
o
r
tio
n
s
o
f
th
e
r
ai
n
y
s
ea
s
o
n
(
Octo
b
er
-
A
p
r
il)
an
d
th
e
d
r
y
s
e
aso
n
(
Ma
y
-
Sep
te
m
b
er
)
o
n
J
av
a
I
s
lan
d
.
T
h
e
ac
cu
r
ac
y
o
f
ea
ch
A
NN
i
s
m
ea
s
u
r
ed
b
y
co
e
f
f
ic
ien
t o
f
d
eter
m
i
n
atio
n
R
2
,
w
h
ic
h
is
ca
lc
u
lated
as
(
4
)
.
2
2
1
10
0%
m
e
as
pr
e
d
pr
e
d
GG
R
G
(
4
)
w
h
er
e
G
meas
is
t
h
e
m
ea
s
u
r
ed
v
alu
e
o
f
t
h
e
s
o
lar
r
ad
iatio
n
an
d
G
pred
is
th
e
es
ti
m
ated
v
al
u
e
o
f
th
e
s
o
lar
r
ad
iatio
n
.
R
2
is
s
elec
ted
as
it
is
o
n
e
o
f
th
e
m
o
s
t
f
r
eq
u
e
n
tl
y
u
s
ed
p
ar
am
eter
s
to
m
ea
s
u
r
e
th
e
ac
c
u
r
ac
y
o
f
s
o
lar
r
ad
iatio
n
p
r
ed
ictio
n
[
9
]
.
T
h
er
ef
o
r
e,
b
y
ca
lcu
lati
n
g
t
h
e
R
2
,
th
e
ac
cu
r
ac
y
o
f
t
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
co
u
ld
ea
s
ily
b
e
co
m
p
ar
ed
w
it
h
th
e
ac
c
u
r
ac
y
o
f
th
e
m
et
h
o
d
s
f
r
o
m
p
r
ev
io
u
s
s
t
u
d
ies.
3
.
1
.
Acc
ura
cy
o
f
da
ily
a
v
er
a
g
e
s
o
la
r
ra
dia
t
io
n e
s
t
i
m
a
t
io
n
T
h
e
ac
cu
r
ac
y
o
f
t
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
w
as
v
alid
ated
b
y
a
m
i
n
i
m
u
m
v
a
lu
e
o
f
R
2
o
f
9
7
.
8
6
%,
as
s
h
o
w
n
in
T
ab
le
3
.
A
h
ig
h
er
v
alu
e
o
f
R
2
i
n
d
icate
s
t
h
at
th
e
est
i
m
a
t
ed
v
al
u
e
is
m
o
r
e
ac
c
u
r
ate;
a
1
0
0
%
v
alu
e
ca
n
b
e
ac
h
iev
ed
if
all
th
e
esti
m
ated
v
alu
es
ar
e
eq
u
al
to
th
e
m
ea
s
u
r
ed
v
al
u
es.
T
h
e
g
r
ap
h
ical
co
m
p
ar
is
o
n
s
o
f
t
h
e
d
ail
y
av
er
ag
e
s
o
lar
r
ad
iatio
n
ar
e
s
h
o
w
n
i
n
Fi
g
u
r
e
s
6
an
d
7
.
T
h
e
est
i
m
atio
n
ac
c
u
r
ac
y
f
o
r
S
u
r
ab
a
y
a
is
h
i
g
h
er
th
a
n
f
o
r
J
ak
ar
ta,
w
h
ich
i
n
d
icate
s
t
h
at
th
e
s
o
lar
r
ad
iatio
n
in
Su
r
a
b
ay
a
i
s
m
o
r
e
p
r
ed
ictab
le
an
d
is
m
o
r
e
s
tr
o
n
g
l
y
co
r
r
elate
d
w
it
h
t
h
e
i
n
p
u
t
p
ar
a
m
eter
s
th
a
n
i
n
J
ak
ar
ta.
I
n
b
o
th
ca
s
e
s
,
t
h
e
est
i
m
a
tio
n
s
f
o
r
J
a
n
u
ar
y
a
n
d
Feb
r
u
ar
y
p
r
o
d
u
ce
s
h
i
g
h
er
er
r
o
r
th
an
f
o
r
th
e
o
t
h
er
m
o
n
t
h
s
.
C
o
n
s
id
er
in
g
th
e
er
r
o
r
d
is
tr
ib
u
tio
n
,
a
n
i
m
p
r
o
v
e
m
en
t
f
o
r
esti
m
atio
n
d
u
r
i
n
g
r
ain
y
s
ea
s
o
n
is
r
ec
o
m
m
e
n
d
ed
f
o
r
th
e
f
u
t
u
r
e
r
esear
ch
.
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:
2
0
8
8
-
8708
Tw
o
-
s
tep
a
r
tifi
cia
l n
eu
r
a
l n
etw
o
r
k
to
esti
ma
te
th
e
s
o
la
r
r
a
d
ia
tio
n
a
t J
a
v
a
I
s
la
n
d
(
A
d
i Ku
r
n
ia
w
a
n
)
3563
T
ab
le
3
.
Daily
a
v
er
ag
e
s
o
lar
r
ad
iatio
n
esti
m
atio
n
ac
c
u
r
ac
y
City
n
G
m
-
m
e
as
G
m
-
pr
e
d
R
2
S
u
r
a
b
a
y
a
1
5
.
0
8
5
.
6
9
9
.
5
5
%
2
4
.
9
6
5
.
6
3
4
.
6
4
4
.
6
7
4
4
.
8
1
4
.
6
6
5
4
.
6
1
4
.
6
3
6
4
.
8
8
5
.
0
4
7
4
.
9
2
4
.
9
0
Jak
a
r
t
a
1
4
.
4
6
5
.
5
1
9
7
.
8
6
%
2
4
.
4
1
5
.
5
1
3
4
.
6
8
4
.
5
7
4
4
.
6
4
5
.
1
4
5
4
.
1
3
4
.
9
3
6
4
.
4
4
4
.
8
3
7
4
.
6
9
4
.
5
1
Fig
u
r
e
6
.
C
o
m
p
ar
is
o
n
o
f
m
ea
s
u
r
ed
an
d
esti
m
ated
d
ail
y
av
er
a
g
e
s
o
lar
r
ad
iatio
n
in
S
u
r
ab
a
y
a
f
o
r
2
0
2
0
Fig
u
r
e
7
.
C
o
m
p
ar
is
o
n
o
f
m
ea
s
u
r
ed
an
d
esti
m
ated
d
ail
y
av
er
ag
e
s
o
lar
r
ad
iatio
n
i
n
J
ak
a
r
ta
f
o
r
2
0
2
0
T
h
e
esti
m
ated
v
a
lu
e
s
o
f
d
ail
y
av
er
ag
e
s
o
lar
r
ad
iatio
n
te
n
d
to
b
e
h
i
g
h
er
t
h
a
n
th
e
m
ea
s
u
r
ed
v
alu
es.
T
h
is
is
d
u
e
to
th
a
t
th
e
m
ea
s
u
r
ed
s
o
lar
r
ad
iatio
n
in
2
0
2
0
is
co
n
s
id
er
ab
l
y
lo
w
er
t
h
an
in
2
0
1
8
-
2
0
1
9
,
w
h
ile
t
h
e
v
alu
e
s
o
f
in
p
u
t
p
ar
a
m
eter
s
te
n
d
to
b
e
eq
u
al.
T
h
e
ac
cu
r
ac
y
o
f
th
e
d
ail
y
a
v
er
ag
e
s
o
lar
r
ad
iatio
n
esti
m
at
io
n
o
n
J
av
a
I
s
l
an
d
m
i
g
h
t
b
e
in
cr
ea
s
ed
if
o
th
er
m
eteo
r
o
lo
g
ical
p
ar
am
eter
s
ar
e
in
v
o
lv
ed
.
P
r
ev
io
u
s
s
tu
d
ie
s
h
a
v
e
in
d
icate
d
th
at
s
u
n
s
h
i
n
e
d
u
r
ati
o
n
an
d
clo
u
d
co
v
er
p
e
r
ce
n
tag
e
s
ig
n
if
ica
n
tl
y
co
r
r
elate
w
it
h
th
e
a
m
o
u
n
t
o
f
s
o
lar
r
ad
iatio
n
[
1
9
,
2
0
]
.
Ho
w
ev
er
,
w
h
ile
th
e
d
ail
y
s
u
n
s
h
i
n
e
d
u
r
atio
n
i
s
m
ea
s
u
r
ed
,
th
e
p
r
e
d
icted
v
alu
e
is
n
o
t
r
ec
o
r
d
e
d
b
y
B
MK
G.
T
h
er
ef
o
r
e,
th
is
p
ar
a
m
eter
co
u
ld
n
o
t
b
e
in
clu
d
ed
as
an
i
n
p
u
t
f
o
r
an
esti
m
ate
o
f
th
e
d
ail
y
av
er
ag
e
s
o
lar
r
ad
iatio
n
f
o
r
th
e
f
o
llo
w
i
n
g
m
o
n
th
.
C
o
m
p
ar
e
d
w
ith
t
h
e
R
2
o
f
th
e
d
ail
y
av
e
r
ag
e
s
o
lar
r
ad
iatio
n
esti
m
ates
f
r
o
m
p
r
ev
io
u
s
s
t
u
d
ie
s
,
th
e
ac
cu
r
ac
y
o
f
t
h
e
p
r
o
p
o
s
e
d
m
et
h
o
d
is
co
m
p
ar
ab
le,
as sh
o
w
n
in
T
ab
le
4
.
T
ab
le
4
.
C
o
m
p
ar
is
o
n
o
f
p
r
o
p
o
s
ed
d
ail
y
av
er
ag
e
s
o
lar
r
ad
iatio
n
esti
m
atio
n
w
i
th
p
r
ev
io
u
s
s
t
u
d
ies
A
u
t
h
o
r
M
e
t
h
o
d
L
o
c
a
t
i
o
n
A
v
e
r
a
g
e
o
f
R
2
P
r
o
p
o
se
d
A
N
N
I
n
d
o
n
e
si
a
9
8
.
7
0
%
M
a
r
z
o
u
q
e
t
a
l
.
[
2
1
]
A
N
N
M
o
r
o
c
c
o
9
7
.
1
6
%
G
u
r
l
e
k
a
n
d
S
a
h
i
n
[
2
2
]
A
N
N
T
u
r
k
e
y
9
8
.
8
8
%
T
e
k
e
a
n
d
Y
i
l
d
i
r
i
m
[
2
3
]
C
u
b
i
c
R
e
g
r
e
ssi
o
n
T
u
r
k
e
y
5
9
.
6
0
%
B
e
h
r
a
n
g
e
t
a
l
.
[
2
4
]
A
N
N
I
r
a
n
9
9
.
5
7
%
3
.
2
.
Acc
ura
cy
o
f
ho
urly
s
o
la
r
r
a
dia
t
io
n e
s
t
i
m
a
t
io
n
T
h
e
m
ea
s
u
r
ed
an
d
esti
m
ated
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
w
a
s
co
m
p
ar
ed
o
n
an
h
o
u
r
l
y
b
asis
f
o
r
an
en
tire
d
ay
f
r
o
m
1
2
AM
to
1
1
:5
9
P
M.
Ho
w
e
v
er
,
in
S
u
r
ab
a
y
a,
th
e
ea
r
lies
t s
u
n
r
i
s
e
is
b
et
w
ee
n
5
A
M
an
d
6
A
M
an
d
t
h
e
latest
s
u
n
s
e
t
i
s
b
et
w
ee
n
5
P
M
an
d
6
P
M
f
o
r
th
e
en
tire
y
ea
r
.
J
ak
ar
ta
h
a
s
a
w
id
er
r
an
g
e
o
f
s
u
n
r
is
e
a
n
d
s
u
n
s
e
t
ti
m
e
s
,
w
it
h
t
h
e
ea
r
lie
s
t
s
u
n
r
is
e
o
cc
u
r
r
in
g
b
et
w
ee
n
5
A
M
a
n
d
7
AM
a
n
d
th
e
lates
t
s
u
n
s
et
o
cc
u
r
r
in
g
b
et
w
ee
n
5
P
M
an
d
7
P
M.
T
h
e
g
r
a
p
h
i
c
a
l
c
o
m
p
a
r
i
s
o
n
s
b
e
t
w
e
e
n
t
h
e
e
s
t
i
m
a
t
e
d
a
n
d
m
e
a
s
u
r
e
d
v
a
l
u
e
s
a
r
e
p
r
e
s
e
n
t
e
d
i
n
F
i
g
u
r
e
s
8
an
d
9
.
T
h
e
h
o
r
izo
n
tal
a
x
is
is
th
e
n
u
m
b
er
o
f
d
ata
p
o
i
n
ts
,
w
h
ic
h
r
e
p
r
esen
ts
th
e
n
u
m
b
er
o
f
t
h
e
h
o
u
r
f
o
r
ea
c
h
m
o
n
t
h
.
Fo
r
ex
a
m
p
le,
d
ata
p
o
in
t
n
u
m
b
er
1
r
ep
r
esen
ts
1
A
M
i
n
J
an
u
a
r
y
,
w
h
ile
d
ata
p
o
in
t
n
u
m
b
er
2
5
r
ep
r
esen
ts
1
A
M
in
Feb
r
u
ar
y
.
A
lt
h
o
u
g
h
th
e
lin
e
s
ar
e
n
o
t
p
er
f
ec
tl
y
eq
u
a
l,
th
e
s
h
ap
es
te
n
d
to
b
e
s
i
m
ilar
.
Un
li
k
e
i
n
d
ail
y
a
v
er
ag
e
esti
m
atio
n
,
th
e
r
es
u
lt
s
o
n
h
o
u
r
l
y
est
i
m
a
tes
ar
e
m
o
r
e
v
ar
ied
.
T
h
e
esti
m
ated
v
al
u
es
i
n
S
u
r
ab
a
y
a
ten
d
to
b
e
h
ig
h
er
,
w
h
ile
th
e
es
ti
m
ated
v
a
lu
es
i
n
J
ak
ar
ta
ten
d
to
b
e
lo
w
er
th
an
t
h
e
m
ea
s
u
r
ed
v
al
u
es.
Sin
ce
b
o
th
o
f
d
ail
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
11
,
No
.
4
,
A
u
g
u
s
t 2
0
2
1
:
3
5
5
9
-
3566
3564
av
er
ag
e
est
i
m
a
tes
i
n
Su
r
ab
a
y
a
an
d
J
ak
ar
ta
ar
e
h
ig
h
er
t
h
an
t
h
e
m
ea
s
u
r
ed
v
alu
e
s
,
th
e
r
esu
lts
o
f
h
o
u
r
l
y
esti
m
atio
n
in
d
icate
th
a
t t
h
er
e
i
s
li
m
itat
io
n
o
f
t
h
e
e
s
ti
m
atio
n
a
cc
u
r
ac
y
w
h
e
n
t
h
e
m
ete
o
r
o
lo
g
i
ca
l in
p
u
t i
s
li
m
i
ted
to
th
e
d
ail
y
a
v
er
ag
e
r
ad
iatio
n
o
n
l
y
.
Fig
u
r
e
s
8
a
n
d
9
also
i
n
d
icate
th
at
li
k
e
i
n
t
h
e
d
ail
y
av
er
ag
e
est
i
m
a
tio
n
,
t
h
e
er
r
o
r
a
r
e
h
ig
h
er
f
o
r
th
e
esti
m
at
io
n
o
n
r
ain
y
s
ea
s
o
n
.
Fig
u
r
e
8
.
C
o
m
p
ar
is
o
n
o
f
m
ea
s
u
r
ed
an
d
esti
m
ated
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
in
S
u
r
ab
a
y
a
f
o
r
2
0
2
0
Fig
u
r
e
9
.
C
o
m
p
ar
is
o
n
o
f
m
ea
s
u
r
ed
an
d
esti
m
ated
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
in
J
ak
ar
t
a
f
o
r
2
0
2
0
T
h
e
R
2
f
o
r
th
e
e
s
ti
m
ated
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
f
o
r
ea
ch
m
o
n
th
ar
e
lis
ted
i
n
T
ab
le
5
.
T
h
e
v
alu
e
s
ar
e
lo
w
er
t
h
an
f
o
r
th
e
d
ail
y
a
v
er
ag
e
s
o
lar
r
ad
iatio
n
b
ec
au
s
e
t
h
e
esti
m
at
io
n
o
f
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
is
m
o
r
e
d
if
f
ic
u
lt.
Fo
r
t
h
e
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
,
th
e
esti
m
atio
n
ac
c
u
r
ac
y
f
o
r
J
ak
ar
ta
is
h
ig
h
er
t
h
a
n
Su
r
ab
a
y
a,
m
ea
n
i
n
g
th
at
t
h
e
co
r
r
elatio
n
b
et
w
ee
n
t
h
e
d
ail
y
a
v
er
ag
e
s
o
lar
r
ad
i
ati
o
n
an
d
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
in
J
ak
ar
ta
is
h
ig
h
er
th
an
in
Su
r
ab
a
y
a.
A
co
m
p
ar
i
s
o
n
o
f
th
e
R
2
ac
h
ie
v
ed
in
p
r
ev
io
u
s
s
t
u
d
ies
w
i
th
th
e
p
r
o
p
o
s
e
d
m
e
t
h
o
d
i
s
s
h
o
w
n
i
n
T
a
b
l
e
6
.
T
h
i
s
c
o
m
p
a
r
i
s
o
n
s
u
g
g
e
s
t
s
t
h
a
t
t
h
e
a
c
c
u
r
a
c
y
o
f
p
r
o
p
o
s
e
d
m
e
t
h
o
d
i
s
h
i
g
h
e
r
t
h
a
n
t
h
a
t
o
f
p
r
e
v
i
o
u
s
s
t
u
d
i
e
s
.
T
ab
le
5
.
Ho
u
r
ly
s
o
lar
r
ad
iatio
n
esti
m
atio
n
ac
cu
r
ac
y
City
n
R
2
S
u
r
a
b
a
y
a
1
9
9
.
4
8
%
2
9
3
.
0
5
%
3
9
4
.
1
8
%
4
9
6
.
6
4
%
5
9
8
.
8
8
%
6
9
8
.
7
1
%
7
9
3
.
8
3
%
Jak
a
r
t
a
1
9
2
.
4
1
%
2
9
7
.
8
7
%
3
9
9
.
4
4
%
4
9
9
.
7
0
%
5
9
9
.
5
0
%
6
9
9
.
5
0
%
7
9
9
.
5
5
%
T
ab
le
6
.
C
o
m
p
ar
is
o
n
o
f
p
r
o
p
o
s
ed
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
esti
m
atio
n
w
i
th
p
r
ev
io
u
s
s
tu
d
ie
s
A
u
t
h
o
r
M
e
t
h
o
d
L
o
c
a
t
i
o
n
A
v
e
r
a
g
e
o
f
R
2
P
r
o
p
o
se
d
A
N
N
I
n
d
o
n
e
si
a
97
.
44
%
L
i
e
t
a
l
.
[
2
5
]
M
A
R
S
H
o
n
g
K
o
n
g
9
1
.
2
3
%
P
a
u
l
e
scu
&
B
l
a
g
a
[
2
6
]
C
l
u
st
e
r
i
n
g
R
o
man
i
a
9
3
%
H
o
c
a
o
g
l
u
&
S
e
r
t
t
a
s
[
2
7
]
M
y
c
i
e
l
sk
i
-
M
a
r
k
o
v
T
u
r
k
e
y
8
4
.
1
3
%
4.
CO
NCLU
SI
O
N
T
h
e
g
o
al
o
f
th
i
s
s
t
u
d
y
w
a
s
to
p
r
o
p
o
s
e
a
m
eth
o
d
to
ac
cu
r
at
el
y
est
i
m
ate
b
o
t
h
th
e
d
ail
y
a
v
er
ag
e
an
d
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
i
n
I
n
d
o
n
esia,
w
h
er
e
t
h
e
o
f
f
icial
m
e
asu
r
e
m
en
t
s
ar
e
n
o
t
a
v
ailab
le
f
r
o
m
B
MK
G.
T
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
n
o
t
o
n
l
y
est
i
m
ate
s
th
e
r
ad
iatio
n
p
r
o
f
ile
f
o
r
ea
ch
m
o
n
t
h
b
ased
o
n
th
e
p
r
ev
io
u
s
h
i
s
to
r
y
b
u
t
also
ca
n
b
e
u
s
ed
to
p
r
ed
ict
d
ail
y
a
v
er
a
g
e
a
n
d
h
o
u
r
l
y
s
o
lar
r
ad
iatio
n
f
o
r
t
h
e
s
u
b
s
eq
u
en
t
m
o
n
t
h
,
u
s
i
n
g
m
eteo
r
o
lo
g
ical
p
ar
a
m
eter
i
n
p
u
ts
a
v
ailab
le
f
r
o
m
B
MK
G.
Du
e
to
t
h
e
u
n
a
v
ailab
ilit
y
o
f
h
o
u
r
l
y
w
ea
th
er
p
ar
am
eter
m
ea
s
u
r
e
m
e
n
ts
,
th
e
esti
m
atio
n
o
f
h
o
u
r
l
y
s
o
lar
r
a
d
iatio
n
is
o
n
l
y
b
ased
o
n
t
h
e
d
ail
y
a
v
er
ag
e
s
o
lar
r
ad
iatio
n
an
d
th
e
ti
m
e
a
n
d
lo
ca
tio
n
in
w
h
ic
h
t
h
e
esti
m
atio
n
is
r
eq
u
ir
ed
.
T
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
is
also
ca
p
ab
le
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:
2
0
8
8
-
8708
Tw
o
-
s
tep
a
r
tifi
cia
l n
eu
r
a
l n
etw
o
r
k
to
esti
ma
te
th
e
s
o
la
r
r
a
d
ia
tio
n
a
t J
a
v
a
I
s
la
n
d
(
A
d
i Ku
r
n
ia
w
a
n
)
3565
o
f
esti
m
ati
n
g
t
h
e
s
o
lar
r
ad
iatio
n
f
o
r
m
u
ltip
le
cit
ies,
at
le
ast
o
n
J
av
a
I
s
lan
d
,
b
y
e
m
p
l
o
y
i
n
g
latit
u
d
e
an
d
lo
n
g
it
u
d
e
as
in
p
u
t
p
ar
a
m
eter
s
.
T
h
e
ac
cu
r
ac
y
o
f
th
e
p
r
o
p
o
s
ed
m
e
th
o
d
h
as
b
ee
n
v
alid
ated
b
y
ca
lcu
lati
n
g
t
h
e
R
2
an
d
co
m
p
ar
in
g
it
w
it
h
t
h
e
r
es
u
lts
f
r
o
m
p
r
ev
io
u
s
s
t
u
d
ies i
n
t
h
e
s
a
m
e
f
ield
o
f
s
t
u
d
y
.
T
h
e
co
m
p
ar
i
s
o
n
s
s
h
o
w
th
at
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
g
en
er
at
es
b
etter
ac
cu
r
ac
y
t
h
an
m
o
s
t
o
f
th
e
r
ef
er
en
ce
s
w
ith
a
v
er
ag
e
R
2
o
f
9
8
.
9
1
%
f
o
r
d
ail
y
av
er
ag
e
est
i
m
at
io
n
an
d
9
7
.
4
4
%
f
o
r
h
o
u
r
l
y
esti
m
atio
n
.
B
ec
au
s
e
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
p
r
o
d
u
ce
d
a
g
r
ea
ter
er
r
o
r
in
th
e
p
ea
k
o
f
th
e
r
ai
n
y
s
ea
s
o
n
th
a
n
i
n
th
e
d
r
y
s
ea
s
o
n
,
it
m
a
y
b
e
p
o
s
s
ib
le
to
i
m
p
r
o
v
e
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
b
y
u
s
i
n
g
a
clu
s
ter
in
g
m
et
h
o
d
th
at
tr
ea
ts
t
h
e
d
r
y
an
d
r
ain
y
s
ea
s
o
n
s
s
ep
ar
atel
y
.
ACK
NO
WL
E
D
G
E
M
E
NT
S
T
h
is
s
tu
d
y
is
f
i
n
an
cia
ll
y
s
u
p
p
o
r
ted
b
y
I
n
s
t
itu
t
T
ek
n
o
lo
g
i
Sep
u
lu
h
No
p
e
m
b
er
b
y
th
e
s
ch
e
m
e
o
f
“
P
en
elit
ian
Da
n
a
Dep
ar
te
m
e
n
”
n
o
.
1
7
3
2
/
P
KS/I
T
S/2
0
2
0
.
RE
F
E
R
E
NC
E
S
[1
]
In
situ
te
f
o
r
Esse
n
ti
a
l
S
e
rv
ice
s
Re
f
o
r
m
,
“
In
d
o
n
e
sia
Clea
n
En
e
rg
y
Ou
tl
o
o
k
:
T
ra
c
k
in
g
P
ro
g
re
ss
a
n
d
Re
v
ie
w
o
f
Cle
a
n
En
e
rg
y
De
v
e
lo
p
m
e
n
t
in
In
d
o
n
e
sia
,
”
J
a
k
a
rta
:
I
n
stit
u
te f
o
r E
ss
e
n
t
ia
l
S
e
rv
ice
s R
e
fo
rm
(
IES
R
)
,
2
0
1
9
.
[2
]
B.
D.
E.
M
a
h
d
i,
H
.
A
b
d
e
latif
,
a
n
d
M
.
A
.
Zaf
ra
n
e
,
“
A
n
in
tera
c
ti
v
e
a
p
p
ro
a
c
h
f
o
r
so
lar
e
n
e
rg
y
s
y
ste
m
:
D
e
sig
n
a
n
d
m
a
n
u
f
a
c
tu
rin
g
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
Co
m
p
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
1
0
,
n
o
.
5
,
p
p
.
4
4
7
8
-
4
4
8
9
,
2
0
2
0
.
[3
]
A
.
Ca
lc
a
b
rin
i,
H.
Zi
a
r,
O.
Isa
b
e
ll
a
,
a
n
d
M
.
Zem
a
n
,
“
A
si
m
p
li
f
ied
sk
y
li
n
e
-
b
a
se
d
m
e
th
o
d
f
o
r
e
stim
a
t
in
g
th
e
a
n
n
u
a
l
so
lar en
e
rg
y
p
o
ten
ti
a
l
in
u
rb
a
n
e
n
v
iro
n
m
e
n
ts,”
Na
tu
re
En
e
rg
y
,
v
o
l.
4
,
n
o
.
3
,
p
p
.
2
0
6
-
2
1
5
,
2
0
1
9
.
[4
]
A
.
Z.
A
b
a
ss
a
n
d
D.
A
.
P
a
v
ly
u
c
h
e
n
k
o
,
“
T
h
e
e
x
p
lo
it
a
ti
o
n
o
f
w
e
ste
r
n
a
n
d
so
u
t
h
e
rn
d
e
se
rts
in
Ira
q
f
o
r
th
e
p
ro
d
u
c
ti
o
n
o
f
so
lar
e
n
e
r
g
y
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
9
,
n
o
.
6
,
p
p
.
4
6
1
7
-
4
6
2
4
,
2
0
1
9
.
[5
]
D.
F
.
A
l
Riz
a
,
S
.
I.
U.
H.
G
il
a
n
i,
a
n
d
M
.
S
.
A
ris,
“
S
tan
d
a
lo
n
e
p
h
o
t
o
v
o
lt
a
ic s
y
ste
m
s
siz
in
g
o
p
ti
m
iz
a
ti
o
n
u
si
n
g
d
e
sig
n
sp
a
c
e
a
p
p
ro
a
c
h
:
Ca
se
stu
d
y
f
o
r
re
sid
e
n
ti
a
l
li
g
h
ti
n
g
lo
a
d
,
”
J
o
u
r
n
a
l
o
f
En
g
in
e
e
rin
g
S
c
ien
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
,
v
o
l.
1
0
,
n
o
.
7
,
p
p
.
9
4
3
-
9
5
7
,
2
0
1
5
.
[6
]
C.
Ya
o
,
M
.
C
h
e
n
,
a
n
d
Y.
-
Y.
H
o
n
g
,
“
No
v
e
l
A
d
a
p
ti
v
e
M
u
lt
i
-
Clu
ste
r
in
g
A
lg
o
rit
h
m
-
Ba
s
e
d
O
p
t
i
m
a
l
E
S
S
S
i
z
i
n
g
i
n
S
h
i
p
P
o
w
e
r
S
y
s
t
e
m
C
o
n
s
i
d
e
r
i
n
g
U
n
c
e
r
t
a
i
n
t
y
,
”
I
E
E
E
T
r
a
n
s
a
c
t
i
o
n
s
o
n
P
o
w
e
r
S
y
s
t
e
m
s
,
v
o
l
.
3
3
,
n
o
.
1
,
p
p
.
3
0
7
-
316
,
2
0
1
8
.
[7
]
A
.
N.
A
z
m
i,
N.
Bin
S
a
li
m
,
a
n
d
A
.
B.
Kh
a
m
is,
“
A
n
a
l
y
sis
o
f
a
n
e
n
e
rg
y
sto
ra
g
e
siz
in
g
f
o
r
g
rid
-
c
o
n
n
e
c
ted
p
h
o
to
v
o
lt
a
ic
sy
ste
m
,
”
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
in
e
e
rin
g
a
n
d
Co
mp
u
ter
S
c
ien
c
e
(
I
J
EE
CS
)
,
v
o
l.
1
6
,
n
o
.
1
,
p
p
.
1
7
-
2
4
,
2
0
1
9
.
[8
]
A
.
Ku
rn
ia
w
a
n
a
n
d
E.
S
h
i
n
tak
u
,
“
De
ter
m
in
in
g
th
e
o
p
ti
m
a
l
in
c
li
n
a
ti
o
n
a
n
d
o
rien
tati
o
n
a
n
g
les
o
f
so
lar
p
a
n
e
ls i
n
sta
ll
e
d
o
n
s
h
ip
,
”
I
n
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Ren
e
wa
b
le
En
e
rg
y
Res
e
a
rc
h
,
v
o
l
.
1
0
,
n
o
.
1
,
p
p
.
4
5
-
5
3
,
2
0
2
0
.
[9
]
M
.
M
a
rz
o
u
q
,
H.
El
F
a
d
il
i,
Z.
L
a
k
h
li
a
i,
a
n
d
K.
Zen
k
o
u
a
r,
“
A
re
v
i
e
w
o
f
so
lar
ra
d
iatio
n
p
re
d
icti
o
n
u
sin
g
a
rti
f
icia
l
n
e
u
ra
l
n
e
tw
o
rk
s,”
2
0
1
7
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
W
ire
les
s
T
e
c
h
n
o
l
o
g
ies
,
Emb
e
d
d
e
d
a
n
d
I
n
tel
li
g
e
n
t
S
y
ste
ms
(
W
IT
S
)
,
F
e
z
,
2
0
1
7
,
p
p
.
1
-
6.
[1
0
]
A
.
Ku
rn
i
a
w
a
n
a
n
d
E.
S
h
in
tak
u
,
“
Esti
m
a
ti
o
n
o
f
th
e
M
o
n
th
ly
G
lo
b
a
l,
Dire
c
t
,
a
n
d
Di
ff
u
se
S
o
lar
Ra
d
iatio
n
in
Ja
p
a
n
Us
in
g
A
rti
f
icia
l
Ne
u
ra
l
Ne
t
w
o
rk
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
M
a
c
h
in
e
L
e
a
r
n
in
g
a
n
d
Co
m
p
u
t
in
g
,
v
o
l.
1
0
,
n
o
.
2
,
p
p
.
2
5
3
-
2
5
8
,
2
0
2
0
.
[1
1
]
G
.
No
tt
o
n
,
C.
Vo
y
a
n
t,
A
.
F
o
u
il
lo
y
,
J.
L
.
Du
c
h
a
u
d
,
a
n
d
M
.
L
.
Niv
e
t,
“
S
o
m
e
a
p
p
li
c
a
ti
o
n
s
o
f
A
NN
to
so
lar
ra
d
iatio
n
e
sti
m
a
ti
o
n
a
n
d
f
o
re
c
a
stin
g
f
o
r
e
n
e
rg
y
a
p
p
li
c
a
ti
o
n
s,”
A
p
p
l
ied
S
c
ie
n
c
e
s
,
v
o
l.
9
,
n
o
.
1
,
2
0
1
9
,
A
rt.
n
o
.
2
0
9
.
[1
2
]
M
.
A
.
Ja
ll
a
l,
S
.
Ch
a
b
a
a
,
a
n
d
A
.
Zero
u
a
l,
“
A
n
e
w
a
rti
f
ici
a
l
m
u
lt
i
-
n
e
u
ra
l
a
p
p
ro
a
c
h
to
e
stim
a
te
th
e
h
o
u
rly
g
lo
b
a
l
so
lar
ra
d
iatio
n
in
a
se
m
i
-
a
rid
c
li
m
a
te si
te,”
T
h
e
o
re
ti
c
a
l
a
n
d
A
p
p
li
e
d
Cl
ima
to
l
o
g
y
,
v
o
l.
1
3
9
,
n
o
.
3
-
4
,
p
p
.
1
2
6
1
-
1
2
7
6
,
2
0
2
0
.
[1
3
]
H.
S
.
Hu
ss
e
in
,
“
G
lo
b
a
l
so
lar
ra
d
iatio
n
p
re
d
icti
o
n
u
sin
g
a
c
o
m
b
in
a
ti
o
n
o
f
su
b
trac
ti
v
e
c
l
u
ste
rin
g
a
lg
o
rit
h
m
a
n
d
a
d
a
p
ti
v
e
n
e
u
ro
-
f
u
z
z
y
in
f
e
r
e
n
c
e
s
y
ste
m
:
A
c
a
s
e
stu
d
y
,
”
J
o
u
rn
a
l
o
f
En
g
i
n
e
e
rin
g
S
c
ie
n
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
,
v
o
l.
1
5
,
n
o
.
3
,
p
p
.
1
6
5
2
-
1
6
6
9
,
2
0
2
0
.
[1
4
]
S
.
S
a
li
su
,
M
.
W
.
M
u
sta
f
a
,
M
.
M
u
sta
p
h
a
,
a
n
d
O.
O.
M
o
h
a
m
m
e
d
,
“
S
o
lar
ra
d
iatio
n
f
o
re
c
a
stin
g
in
Nig
e
ria
b
a
se
d
o
n
h
y
b
rid
P
S
O
-
A
NFIS
a
n
d
W
T
-
AN
F
IS
a
p
p
r
o
a
c
h
,
”
I
n
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
ter
En
g
i
n
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
9
,
n
o
.
6
,
p
p
.
3
9
1
6
-
3
9
2
6
,
2
0
1
9
.
[1
5
]
A
.
A
.
F
ird
a
u
s,
R.
T
.
Yu
n
a
rd
i,
E
.
I.
A
g
u
stin
,
T
.
E.
P
u
tri
,
a
n
d
D.
O.
A
n
g
g
ria
wa
n
,
“
S
h
o
rt
-
term
p
h
o
to
v
o
lt
a
ics
p
o
w
e
r
f
o
re
c
a
stin
g
u
sin
g
Jo
r
d
a
n
re
c
u
rre
n
t
n
e
u
ra
l
n
e
tw
o
rk
in
S
u
ra
b
a
y
a
,
”
T
EL
KOM
NIKA
T
e
lec
o
mm
u
n
ic
a
ti
o
n
,
Co
mp
u
ti
n
g
,
El
e
c
tro
n
ics
a
n
d
C
o
n
tro
l
,
v
o
l.
1
8
,
n
o
.
2
,
p
p
.
1
0
8
9
-
1
0
9
4
,
2
0
2
0
.
[1
6
]
A
.
Kh
o
sra
v
i,
R.
N.
N.
Ko
u
ry
,
L
.
M
a
c
h
a
d
o
,
a
n
d
J.
J.
G
.
P
a
b
o
n
,
“
P
re
d
ictio
n
o
f
h
o
u
rly
so
lar
ra
d
iatio
n
i
n
A
b
u
M
u
sa
Isla
n
d
u
si
n
g
m
a
c
h
in
e
lea
rn
in
g
a
lg
o
rit
h
m
s,”
J
o
u
rn
a
l
o
f
Clea
n
e
r P
ro
d
u
c
ti
o
n
,
v
o
l.
1
7
6
,
p
p
.
6
3
-
7
5
,
2
0
1
8
.
[1
7
]
J.
He
a
to
n
,
“
A
rti
f
icia
l
In
telli
g
e
n
c
e
f
o
r
Hu
m
a
n
s,
”
V
o
lu
m
e
3
:
De
e
p
L
e
a
rn
in
g
a
n
d
Ne
u
ra
l
Ne
tw
o
rk
s
,”
Ch
e
ste
rfield
:
He
a
to
n
Res
e
a
rc
h
,
In
c
,
2
0
1
5
.
[1
8
]
A
.
Ku
rn
ia
w
a
n
a
n
d
E.
S
h
in
tak
u
,
“
A
Ne
u
ra
l
N
e
t
w
o
rk
-
Ba
se
d
R
a
p
id
M
a
x
im
u
m
P
o
w
e
r
P
o
i
n
t
T
ra
c
k
i
n
g
M
e
th
o
d
f
o
r
P
h
o
t
o
v
o
lt
a
ic S
y
ste
m
s in
P
a
rt
ial
S
h
a
d
in
g
C
o
n
d
it
i
o
n
s,”
A
p
p
l
ied
S
o
l
a
r E
n
e
rg
y
,
v
o
l.
5
6
,
n
o
.
3
,
p
p
.
1
5
7
-
1
6
7
,
2
0
2
0
.
[1
9
]
K.
Bo
u
c
h
o
u
ich
a
,
N.
Ba
il
e
k
,
M
.
E.
S
.
M
a
h
m
o
u
d
,
J.
A
.
A
lo
n
so
,
A.
S
li
m
a
n
i,
a
n
d
A
b
d
a
ll
a
h
Dja
a
f
a
ri,
“
Esti
m
a
ti
o
n
o
f
M
o
n
t
h
ly
Av
e
ra
g
e
Da
il
y
G
lo
b
a
l
S
o
lar
Ra
d
iat
io
n
Us
in
g
M
e
teo
ro
l
o
g
ica
l
-
Ba
s
e
d
M
o
d
e
ls
i
n
A
d
ra
r,
A
lg
e
ria,”
Ap
p
li
e
d
S
o
l
a
r E
n
e
rg
y
,
v
o
l.
5
4
,
n
o
.
6
,
p
p
.
4
4
8
-
45
5
,
2
0
1
8
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
11
,
No
.
4
,
A
u
g
u
s
t 2
0
2
1
:
3
5
5
9
-
3566
3566
[2
0
]
A
.
Ko
c
a
,
H.
F
.
Oz
to
p
,
Y.
V
a
ro
l,
a
n
d
G
.
O.
Ko
c
a
,
“
Esti
m
a
ti
o
n
o
f
so
lar rad
iatio
n
u
sin
g
a
rti
f
icia
l
n
e
u
ra
l
n
e
tw
o
rk
s
w
it
h
d
if
fe
re
n
t
in
p
u
t
p
a
ra
m
e
ters
f
o
r
M
e
d
it
e
rra
n
e
a
n
re
g
io
n
o
f
A
n
a
to
li
a
in
T
u
rk
e
y
,
”
Exp
e
rt
S
y
ste
ms
wit
h
Ap
p
l
ica
ti
o
n
s
,
v
o
l.
3
8
,
n
o
.
7
,
p
p
.
8
7
5
6
-
8
7
6
2
,
2
0
1
1
.
[2
1
]
M
.
M
a
rz
o
u
q
,
Z.
B
o
u
n
o
u
a
,
A
.
M
e
c
h
a
q
ra
n
e
,
H.
E.
F
a
d
il
i,
Z.
L
a
k
h
li
a
i,
a
n
d
K.
Zen
k
o
u
a
r,
“
A
NN
-
b
a
se
d
m
o
d
e
ll
in
g
a
n
d
p
re
d
ictio
n
o
f
d
a
il
y
g
lo
b
a
l
so
lar
ir
ra
d
iatio
n
u
si
n
g
c
o
m
m
o
n
l
y
m
e
a
su
re
d
m
e
teo
ro
lo
g
ica
l
p
a
ra
m
e
ters
,
”
I
OP
Co
n
fer
e
n
c
e
S
e
rie
s: E
a
rth
a
n
d
E
n
v
iro
n
me
n
ta
l
S
c
ien
c
e
,
v
o
l.
1
6
1
,
n
o
.
1
,
2
0
1
8
.
[2
2
]
C.
G
u
rlek
a
n
d
M
.
S
a
h
i
n
,
“
Esti
m
a
ti
o
n
o
f
th
e
G
lo
b
a
l
S
o
lar
Ra
d
iatio
n
w
it
h
th
e
A
rti
f
icia
l
Ne
u
ra
l
Ne
t
w
o
rk
s
f
o
r
th
e
Cit
y
o
f
S
iv
a
s,”
Eu
ro
p
e
a
n
M
e
c
h
a
n
ic
a
l
S
c
ien
c
e
,
v
o
l.
2
,
n
o
.
2
,
p
p
.
4
6
-
5
1
,
2
0
1
8
.
[2
3
]
A
.
Tek
e
a
n
d
H.
B.
Yi
ld
i
rim
,
“
Esti
m
a
ti
n
g
th
e
m
o
n
th
ly
g
lo
b
a
l
so
l
a
r
ra
d
iatio
n
f
o
r
Eas
tern
M
e
d
i
terra
n
e
a
n
Re
g
io
n
,
”
En
e
rg
y
Co
n
v
e
rs
io
n
a
n
d
M
a
n
a
g
e
me
n
t
,
v
o
l.
8
7
,
p
p
.
6
2
8
-
6
3
5
,
2
0
1
4
.
[2
4
]
M
.
A
.
Be
h
ra
n
g
,
E.
A
ss
a
r
e
h
,
A
.
Gh
a
n
b
a
rz
a
d
e
h
,
a
n
d
A
.
R.
No
g
h
re
h
a
b
a
d
i,
“
T
h
e
p
o
ten
ti
a
l
o
f
d
if
f
e
r
e
n
t
a
rti
f
icia
l
n
e
u
ra
l
n
e
tw
o
rk
(AN
N)
tec
h
n
iq
u
e
s
in
d
a
il
y
g
lo
b
a
l
so
lar
ra
d
iati
o
n
m
o
d
e
li
n
g
b
a
se
d
o
n
m
e
teo
ro
lo
g
ica
l
d
a
ta,”
S
o
la
r
En
e
rg
y
,
v
o
l.
8
4
,
n
o
.
8
,
p
p
.
1
4
6
8
-
1
4
8
0
,
2
0
1
0
.
[2
5
]
D.
H.
W
.
L
i,
W
.
Ch
e
n
,
S
.
L
i,
a
n
d
S
.
L
o
u
,
“
Esti
m
a
ti
o
n
o
f
h
o
u
rly
g
l
o
b
a
l
so
lar
ra
d
iati
o
n
u
sin
g
M
u
lt
iv
a
ri
a
te
A
d
a
p
ti
v
e
Re
g
re
ss
io
n
S
p
li
n
e
(M
A
RS
)
-
A
c
a
s
e
stu
d
y
o
f
Ho
n
g
Ko
n
g
,
”
En
e
rg
y
,
v
o
l.
1
8
6
,
2
0
1
9
,
A
rt
.
n
o
.
1
1
5
8
5
7
.
[2
6
]
E.
P
a
u
les
c
u
a
n
d
R.
Blag
a
,
“
Re
g
re
ss
io
n
m
o
d
e
ls
f
o
r
h
o
u
r
ly
d
iffu
se
so
lar
ra
d
iatio
n
,
”
S
o
la
r
E
n
e
rg
y
,
v
o
l.
1
2
5
,
p
p
.
1
1
1
-
1
2
4
,
2
0
1
6
.
[2
7
]
F
.
O.
Ho
c
a
o
g
lu
a
n
d
F
.
S
e
rtt
a
s,
“
A
n
o
v
e
l
h
y
b
rid
(M
y
c
ielsk
i
-
M
a
rk
o
v
)
m
o
d
e
l
f
o
r
h
o
u
rly
so
lar
ra
d
iatio
n
f
o
re
c
a
stin
g
,
”
Ren
e
wa
b
le E
n
e
rg
y
,
v
o
l.
1
0
8
,
p
p
.
6
3
5
-
6
4
3
,
2
0
1
7
.
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
Ad
i
K
u
r
n
ia
w
a
n
wa
s
b
o
rn
i
n
S
u
r
a
b
a
y
a
,
In
d
o
n
e
sia
in
1
9
8
9
.
He
re
c
e
iv
e
d
th
e
B.
En
g
.
a
n
d
M
.
En
g
.
d
e
g
re
e
s
in
e
le
c
tri
c
a
l
e
n
g
in
e
e
rin
g
,
p
o
w
e
r
s
y
ste
m
s,
f
ro
m
In
stit
u
t
T
e
k
n
o
lo
g
i
S
e
p
u
l
u
h
No
p
e
m
b
e
r
(IT
S
),
S
u
ra
b
a
y
a
,
In
d
o
n
e
sia
,
in
2
0
1
1
a
n
d
2
0
1
3
,
re
sp
e
c
ti
v
e
ly
.
He
re
c
e
iv
e
d
th
e
Dr.E
n
g
.
De
g
r
e
es
f
ro
m
D
e
p
a
rt
m
e
n
t
o
f
T
r
a
n
sp
o
rtati
o
n
a
n
d
E
n
v
iro
n
m
e
n
tal
S
y
ste
m
s,
Hiro
sh
im
a
Un
iv
e
r
sit
y
,
Ja
p
a
n
,
in
2
0
2
0
.
He
is
n
o
w
th
e
h
e
a
d
o
f
M
a
rin
e
El
e
c
tri
c
a
l
a
n
d
A
u
to
m
a
ti
o
n
S
y
ste
m
s
L
a
b
o
ra
to
ry
in
De
p
a
rtme
n
t
o
f
M
a
rin
e
En
g
in
e
e
ri
n
g
o
f
I
T
S
,
in
w
h
ich
h
e
h
a
s
b
e
e
n
a
lec
tu
re
r
sin
c
e
2
0
1
4
.
His
re
se
a
rc
h
in
tere
st
in
c
lu
d
e
s
re
n
e
wa
b
le
e
n
e
rg
y
s
y
st
e
m
s
a
n
d
c
o
n
tro
l
o
f
p
o
w
e
r
c
o
n
v
e
rters
.
He
is
c
u
rre
n
tl
y
w
o
rk
in
g
to
w
a
rd
h
ig
h
e
ff
ici
e
n
c
y
m
a
x
i
m
u
m
p
o
w
e
r
trac
k
in
g
f
o
r
P
V
sy
ste
m
f
o
r
sh
ip
a
p
p
li
c
a
ti
o
n
.
Eiji
S
h
in
ta
k
u
w
a
s
b
o
rn
in
Hy
o
g
o
,
Ja
p
a
n
in
1
9
6
6
.
He
re
c
e
iv
e
d
th
e
B.
E.
,
M
.
E.
a
n
d
Dr.
En
g
.
d
e
g
re
e
s in
n
a
v
a
l
a
rc
h
it
e
c
t
f
ro
m
K
y
u
sh
u
Un
iv
e
rsit
y
,
Ja
p
a
n
,
in
1
9
8
9
,
1
9
9
1
a
n
d
1
9
9
5
,
re
sp
e
c
ti
v
e
ly
.
He
is
a
n
A
s
so
c
iate
P
ro
f
e
ss
o
r
a
t
th
e
De
p
a
rtm
e
n
t
o
f
T
ra
n
sp
o
rtatio
n
a
n
d
E
n
v
iro
n
m
e
n
tal
S
y
ste
m
s,
Hiro
sh
im
a
Un
iv
e
rsit
y
,
Ja
p
a
n
.
His res
e
a
rc
h
in
tere
sts in
c
lu
d
e
d
e
v
e
lo
p
m
e
n
t
o
f
stru
c
tu
ra
l
m
o
n
it
o
ri
n
g
d
e
v
ice
s
f
o
r
larg
e
s
c
a
le
stru
c
tu
re
,
c
o
n
tro
l
o
f
m
a
rin
e
e
q
u
ip
m
e
n
t,
e
lec
tri
c
p
ro
p
u
lsio
n
sy
ste
m
f
o
r
sh
ip
.
He
is
a
m
e
m
b
e
r
o
f
T
h
e
Ja
p
a
n
S
o
c
iety
o
f
Na
v
a
l
A
rc
h
it
e
c
ts
a
n
d
Oc
e
a
n
En
g
i
n
e
e
rs,
T
h
e
Ja
p
a
n
In
stit
u
te
o
f
M
a
rin
e
E
n
g
in
e
e
rin
g
a
n
d
T
h
e
Ro
b
o
ti
c
s S
o
c
iety
o
f
Ja
p
a
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.