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u
c
h
as
T
R
A
NSYS
[
6
]
,
R
ad
ian
ce
,
E
SP
-
r
a
n
d
o
th
er
s
i
n
cl
u
d
in
g
al
g
o
r
ith
m
ic
o
p
ti
m
izatio
n
en
g
i
n
e
s
u
c
h
a
s
M
atlab
.
T
h
e
ad
v
an
ce
m
en
t
i
n
co
m
p
u
ter
tec
h
n
o
lo
g
ie
s
h
as
m
ad
e
th
e
ap
p
licatio
n
o
f
n
u
m
er
ica
l
o
p
ti
m
izatio
n
at
ea
s
e
s
in
ce
1
9
8
0
s
.
Sin
ce
th
e
n
,
B
E
S
h
av
e
b
ee
n
m
o
d
elled
in
ter
m
o
f
m
at
h
e
m
ati
ca
l
/e
m
p
ir
ical
E
q
u
atio
n
s
w
h
ic
h
o
b
tain
ed
th
r
o
u
g
h
r
i
g
o
r
o
u
s
en
er
g
y
s
i
m
u
latio
n
.
E
v
o
lu
tio
n
ar
y
Alg
o
r
it
h
m
s
(
E
As)
ar
e
n
e
w
k
in
d
s
o
f
m
o
d
er
n
o
p
ti
m
izatio
n
alg
o
r
it
h
m
s
t
h
at
i
n
s
p
ir
ed
b
y
p
r
in
cip
le
o
f
n
at
u
r
e
e
v
o
lu
tio
n
.
E
As
h
av
e
s
o
m
e
ad
v
a
n
ta
g
es
o
v
er
th
e
tr
ad
itio
n
al
o
p
ti
m
izatio
n
alg
o
r
ith
m
s
a
n
d
ar
e
o
f
th
e
g
r
ea
t
i
m
p
o
r
tan
ce
a
n
d
h
av
e
a
w
id
e
r
an
g
e
o
f
ap
p
li
ca
tio
n
s
.
T
h
e
tr
ad
itio
n
al
o
p
tim
izatio
n
alg
o
r
it
h
m
s
u
s
u
all
y
h
a
v
e
s
tr
ict
li
m
itatio
n
o
n
th
e
f
u
n
c
tio
n
s
s
u
c
h
as
th
e
ir
d
if
f
er
e
n
tiab
ilit
y
;
h
o
w
e
v
er
,
E
As
d
o
n
o
t
r
eq
u
ir
e
th
e
d
if
f
er
e
n
tiab
ilit
y
o
f
t
h
e
f
u
n
cti
o
n
s
an
d
h
a
v
e
p
ar
allel
p
r
o
p
er
t
y
.
T
h
er
e
f
o
r
e,
th
e
y
ar
e
o
f
ten
u
s
ed
to
s
o
lv
e
s
o
m
e
co
m
p
le
x
,
lar
g
e
s
ca
le,
n
o
n
li
n
ea
r
an
d
n
o
n
-
d
i
f
f
er
e
n
tiab
le
o
p
tim
izatio
n
p
r
o
b
le
m
s
.
T
h
er
e
ar
e
v
ar
ieties
o
f
o
p
tim
izatio
n
al
g
o
r
it
h
m
th
at
h
a
s
b
ee
n
d
ev
elo
p
ed
s
u
c
h
a
s
A
r
ti
f
icial
B
ee
C
o
lo
n
y
(
A
B
C
)
[
7
]
,
Gen
etic
Alg
o
r
it
h
m
s
(
GA
)
[
8
]
,
p
ar
ticles
w
ar
m
o
p
tim
is
atio
n
(
P
SO)
[
9
]
an
d
o
th
er
s
w
h
ic
h
h
a
s
its
o
w
n
s
p
ec
if
icatio
n
an
d
ch
ar
ac
ter
is
tic.
Fu
r
t
h
er
m
o
r
e,
a
co
m
b
in
at
io
n
o
f
o
n
e
o
r
f
e
w
alg
o
r
ith
m
s
as
a
h
y
b
r
id
al
g
o
r
ith
m
al
s
o
h
a
s
b
ee
n
in
tr
o
d
u
ce
d
to
i
m
p
r
o
v
e
th
e
p
r
ev
io
u
s
v
er
s
io
n
in
ter
m
o
f
s
p
ee
d
an
d
d
ata
p
r
o
ce
s
s
in
g
.
E
As
ar
e
s
ea
r
ch
an
d
o
p
tim
izatio
n
tec
h
n
iq
u
es
b
ase
d
o
n
th
e
p
r
in
cip
al
o
f
n
at
u
r
al
ev
o
lu
tio
n
.
T
h
er
e
ar
e
f
o
u
r
m
ain
s
tr
ea
m
s
i
n
ev
o
lu
tio
n
ar
y
al
g
o
r
ith
m
s
n
a
m
e
l
y
Gen
et
ic
A
l
g
o
r
it
h
m
s
(
GA
)
,
Gen
etic
P
r
o
g
r
a
m
m
in
g
(
GP
)
,
E
v
o
lu
tio
n
Stra
teg
ies
(
E
S)
an
d
E
v
o
lu
tio
n
ar
y
P
r
o
g
r
am
m
in
g
(
E
P
)
.
T
h
is
p
ap
er
p
r
esen
ts
an
a
u
to
m
ated
ca
lib
r
atio
n
o
f
s
i
m
u
lated
b
aselin
e
en
er
g
y
f
o
r
a
g
r
ee
n
h
o
u
s
e
s
y
s
te
m
u
s
i
n
g
E
v
o
lu
tio
n
ar
y
P
r
o
g
r
a
m
m
i
n
g
(
E
P
)
at
m
in
i
m
u
m
er
r
o
r
b
et
w
ee
n
s
i
m
u
lated
an
d
m
ea
s
u
r
ed
en
er
g
y
u
s
e.
An
o
p
tim
izatio
n
-
b
ased
s
i
m
u
la
tio
n
i
s
c
h
o
s
e
n
a
n
d
ca
r
r
ied
o
u
t
b
y
co
u
p
li
n
g
t
h
e
o
p
ti
m
izatio
n
alg
o
r
it
h
m
e
n
g
i
n
e
,
Ma
tlab
an
d
E
n
er
g
y
P
lu
s
w
it
h
E
P
to
d
eter
m
i
n
e
b
aseli
n
e
e
n
er
g
y
at
m
i
n
i
m
al
er
r
o
r
.
B
C
VT
B
i
s
u
s
ed
to
co
u
p
le
t
h
e
E
n
er
g
y
-
p
l
u
s
w
it
h
Ma
tlab
u
s
i
n
g
P
to
le
m
y
I
I
en
v
ir
o
n
m
e
n
t.
A
s
in
g
le
o
b
j
ec
tiv
e
f
u
n
ctio
n
i
s
d
ef
i
n
ed
an
d
s
e
t
i
n
t
h
e
E
P
to
m
i
n
i
m
ized
er
r
o
r
b
et
w
ee
n
s
i
m
u
lated
a
n
d
m
ea
s
u
r
ed
en
er
g
y
f
r
o
m
th
e
g
r
ee
n
h
o
u
s
e.
F
u
r
th
er
m
o
r
e,
th
r
ee
v
ar
iab
le
s
ar
e
r
an
d
o
m
ize
d
f
o
r
in
it
ializatio
n
p
r
o
ce
s
s
to
s
ea
r
ch
f
o
r
a
d
esire
d
g
r
o
u
p
o
f
p
o
p
u
latio
n
s
u
ch
as
th
e
o
p
er
atin
g
h
o
u
r
s
o
f
a
x
i
al
f
a
n
,
e
x
h
au
s
t
f
a
n
a
n
d
ir
r
ig
a
t
io
n
p
u
m
p
.
T
h
e
g
r
ee
n
h
o
u
s
e
b
u
ild
in
g
lo
ca
ted
in
Un
i
v
er
s
iti P
u
tr
a
Ma
la
y
s
ia
(
UP
M)
ca
m
p
u
s
i
s
u
s
ed
as a
ca
s
e
s
t
u
d
y
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
T
h
e
m
eth
o
d
o
lo
g
y
i
n
t
h
is
s
t
u
d
y
co
m
p
r
i
s
es
o
f
s
ix
s
ta
g
es
i.e
.
1
)
p
r
o
j
ec
t
o
v
er
all
f
r
a
m
e
w
o
r
k
,
2
)
g
r
ee
n
h
o
u
s
e
m
o
d
elli
n
g
,
3
)
E
P
alg
o
r
ith
m
d
ev
elo
p
m
e
n
t,
4
)
b
u
ild
in
g
en
er
g
y
s
i
m
u
lato
r
5
)
ca
lib
r
atio
n
p
r
o
ce
s
s
an
d
6
)
b
u
ild
in
g
e
n
er
g
y
ev
al
u
at
io
n
.
2
.
1
.
P
r
o
j
ec
t
O
v
er
a
ll F
r
a
m
e
w
o
rk
T
h
e
o
v
er
all
p
r
o
j
ec
t
f
r
am
e
w
o
r
k
s
tar
ts
w
i
th
m
o
d
elli
n
g
t
h
e
g
r
ee
n
h
o
u
s
e
s
y
s
te
m
u
s
i
n
g
O
p
en
St
u
d
io
Sk
etc
h
Up
.
T
h
e
en
er
g
y
s
i
m
u
la
tio
n
is
ca
r
r
ied
o
u
t
b
y
u
s
i
n
g
E
n
er
g
y
P
l
u
s
.
T
h
e
E
n
er
g
y
P
l
u
s
i
s
u
s
ed
to
b
u
i
ld
th
e
g
r
ee
n
h
o
u
s
e
m
o
d
el
b
y
k
e
y
-
i
n
th
e
b
u
ild
in
g
d
ata
s
u
ch
a
s
b
u
ild
in
g
p
ar
a
m
eter
s
,
H
V
AC
s
et
u
p
,
elec
tr
ical
eq
u
ip
m
e
n
t
an
d
etc.
i
n
t
h
e
s
o
f
t
w
ar
e.
Me
a
n
w
h
il
e,
E
v
o
l
u
tio
n
ar
y
P
r
o
g
r
a
m
m
in
g
(
E
P
)
p
r
o
g
r
am
ed
in
th
e
Ma
tlab
is
u
s
ed
to
o
p
ti
m
ize
t
h
e
ca
lib
r
atio
n
p
r
o
ce
s
s
i
n
g
etti
n
g
t
h
e
m
in
i
m
u
m
er
r
o
r
.
E
P
co
m
p
r
is
es
o
f
f
o
u
r
d
if
f
er
en
t
p
h
ase
s
i.e
.
1
)
in
itializat
io
n
,
2
)
m
u
ta
tio
n
a
n
d
ev
al
u
atio
n
,
3
)
co
m
b
in
atio
n
,
s
elec
tio
n
an
d
n
e
w
g
en
er
atio
n
a
n
d
4
)
co
n
v
er
g
e
n
ce
tes
t.
T
o
b
u
ild
an
ac
c
u
r
ate
g
r
ee
n
h
o
u
s
e
e
n
er
g
y
m
o
d
el,
th
e
m
o
d
el
m
u
s
t
p
as
s
a
ca
lib
r
atio
n
p
r
o
ce
s
s
.
T
h
is
i
s
p
er
f
o
r
m
ed
b
y
e
n
s
u
r
i
n
g
th
e
d
i
f
f
er
en
ce
b
et
w
ee
n
s
i
m
u
lated
an
d
m
ea
s
u
r
ed
en
er
g
y
d
ata
is
w
i
t
h
in
a
s
p
ec
if
ied
er
r
o
r
b
y
I
P
MV
P
p
r
o
to
co
l.
T
h
e
ca
lib
r
atio
n
in
v
o
lv
e
s
an
i
ter
ativ
e
p
r
o
ce
s
s
to
f
i
n
d
th
e
b
es
t
v
ar
iab
l
es
co
n
f
ig
u
r
atio
n
in
th
e
g
r
ee
n
h
o
u
s
e
m
o
d
el
to
m
in
i
m
ize
er
r
o
r
b
et
w
ee
n
s
i
m
u
late
d
an
d
m
ea
s
u
r
ed
e
n
er
g
y
u
s
e
o
f
t
h
e
g
r
ee
n
h
o
u
s
e.
T
h
e
v
ar
iab
les
ar
e
th
e
o
p
er
atin
g
h
o
u
r
s
o
f
ex
h
a
u
s
t
f
a
n
,
ax
ial
f
a
n
a
n
d
w
a
ter
p
u
m
p
f
o
r
ir
r
ig
atio
n
s
y
s
te
m
.
B
u
ild
in
g
C
o
n
tr
o
l
Vir
tu
al
T
est
B
ed
(
B
C
V
T
B
)
is
u
s
ed
as
a
m
id
d
le
to
o
l
f
o
r
th
e
Ma
tlab
an
d
E
n
er
g
y
P
lu
s
.
T
h
e
ca
lib
r
ated
m
o
d
el
is
th
e
n
u
s
ed
to
esti
m
ate
e
n
er
g
y
s
a
v
i
n
g
s
f
r
o
m
s
e
v
er
al
r
etr
o
f
it p
r
o
j
ec
t.
2
.
2
.
M
o
dellin
g
T
h
e
g
r
e
en
h
o
u
s
e
m
o
d
el
is
s
e
tu
p
in
s
u
ch
th
at
th
e
e
n
er
g
y
co
n
s
u
m
p
tio
n
w
ill
r
ep
r
esen
t
th
e
ac
t
u
al
g
r
ee
n
h
o
u
s
e.
W
ith
t
h
e
a
v
ailab
le
o
f
C
o
m
p
u
ter
A
id
ed
Desi
g
n
(
C
A
D)
s
o
f
t
w
ar
e
a
n
d
Gr
ap
h
ical
User
I
n
ter
f
ac
e
(
GUI
)
,
th
e
g
r
ee
n
h
o
u
s
e
m
o
d
el
ca
n
b
e
ea
s
i
l
y
d
r
a
w
n
in
3
D
an
d
th
e
t
h
er
m
al
z
o
n
e
s
et
tin
g
ca
n
b
e
ea
s
il
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l
.
1
2
,
No
.
2
,
No
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er
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8
:
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4
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–
6
5
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ip
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T
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ato
Gr
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g
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r
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Fig
u
r
e
2
s
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ild
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Fig
u
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atic
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E
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u
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ased
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e
n
er
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d
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w
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ich
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u
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ch
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Fig
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s
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ical
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a)
I
n
itializatio
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P
h
ase:
T
h
e
i
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itia
lizatio
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p
h
a
s
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n
t
h
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ized
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n
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ater
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t
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m
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h
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g
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n
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ain
t
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ase
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h
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co
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ed
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ate
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u
m
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d
co
n
s
tr
ain
ed
ar
e
in
E
q
u
atio
n
s
(
1
)
an
d
(
2
)
:
(
)
(
1
)
(
2
)
w
h
er
e
K
is
t
h
e
n
u
m
b
er
o
f
r
o
w
,
L
is
t
h
e
n
u
m
b
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f
co
l
u
m
n
,
A
is
th
e
o
f
f
s
et,
B
is
th
e
m
in
i
m
u
m
r
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d
o
m
,
f
i is t
h
e
s
i
m
u
lated
e
n
er
g
y
g
e
n
er
ated
f
r
o
m
r
a
n
d
o
m
co
n
f
i
g
u
r
atio
n
,
f
m
ax
is
t
h
e
m
o
n
ito
r
ed
en
er
g
y
in
t
h
e
b
u
ild
i
n
g
,
a
n
d
f
m
i
n
is
t
h
e
m
in
i
m
u
m
ac
ce
p
tab
le
s
i
m
u
lated
en
er
g
y
.
T
h
e
in
i
tial
izatio
n
p
h
ase
w
a
s
p
r
e
-
s
et
to
r
u
n
1
,
0
0
0
lo
o
p
s
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r
u
n
t
il 2
0
in
itial c
o
n
f
i
g
u
r
atio
n
s
“
p
ar
en
t
s
”
s
ati
s
f
ied
th
e
d
ef
i
n
ed
co
n
s
tr
ain
ed
.
b)
Mu
tatio
n
an
d
E
v
a
l
u
atio
n
P
h
a
s
e:
T
h
e
m
u
tatio
n
p
h
a
s
e
is
to
g
en
er
ate
m
u
tated
p
o
p
u
latio
n
“
o
f
f
s
p
r
in
g
”
f
r
o
m
th
e
p
ar
en
t
‟
s
p
o
p
u
latio
n
.
T
h
er
e
ar
e
v
ar
ietie
s
o
f
m
u
tati
o
n
o
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r
f
o
r
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P
,
h
o
w
e
v
er
th
is
s
t
u
d
y
w
il
l
u
s
e
Gau
s
s
ia
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m
u
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as i
n
class
i
c
E
P
.
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h
e
Gau
s
s
ia
n
f
o
r
m
u
la
i
s
as in
E
q
u
atio
n
(
3
)
.
(
)
(
)
(
3
)
w
h
er
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Xi+
m
,
j
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th
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f
f
s
p
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g
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j
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p
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β
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s
ea
r
ch
s
tep
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m
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m
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m
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f
i
is
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x
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d
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x
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x
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m
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m
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it
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th
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s
p
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ase
2
0
m
u
tate
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co
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f
i
g
u
r
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w
i
ll
b
e
g
e
n
er
ate.
T
h
e
f
it
n
es
s
v
alu
e
s
o
r
also
th
e
o
b
j
ec
tiv
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f
u
n
ctio
n
s
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n
th
e
al
g
o
r
ith
m
is
to
m
i
n
i
m
is
e
th
e
er
r
o
r
o
f
e
n
er
g
y
in
t
h
e
s
y
s
te
m
w
h
ic
h
ev
a
lu
at
ed
u
s
i
n
g
NM
B
E
an
d
C
V
(
R
MSE
)
as
s
h
o
w
n
i
n
E
q
u
atio
n
(
5
)
an
d
(
6
)
.
c)
C
o
m
b
i
n
atio
n
,
Select
io
n
an
d
Ne
w
Ge
n
er
atio
n
P
h
a
s
e:
W
h
e
n
n
e
w
m
u
tated
o
f
f
s
p
r
in
g
g
e
n
er
ated
,
th
e
p
ar
en
ts
an
d
t
h
e
o
f
f
s
p
r
i
n
g
s
ar
e
co
m
b
i
n
ed
in
s
er
ies
to
f
o
r
m
a
g
r
o
u
p
o
f
4
0
p
o
p
u
latio
n
s
.
T
h
e
p
o
p
u
latio
n
w
ill
th
e
n
s
o
r
t
an
d
r
an
k
ac
co
r
d
in
g
to
th
eir
f
it
n
ess
v
al
u
e
i
n
d
escen
d
i
n
g
o
r
d
er
.
T
h
e
to
p
2
0
o
f
th
e
p
o
p
u
latio
n
,
ar
e
th
e
n
s
elec
ted
an
d
ca
r
r
ied
f
o
r
w
ar
d
to
f
o
r
m
n
e
w
p
ar
en
t
s
‟
g
e
n
er
atio
n
.
d)
C
o
n
v
er
g
e
n
ce
T
est
P
h
ase:
C
o
n
v
er
g
e
n
ce
test
i
s
to
d
eter
m
i
n
e
t
h
e
s
to
p
p
in
g
cr
iter
io
n
o
f
t
h
e
s
i
m
u
latio
n
.
I
f
th
e
d
i
f
f
er
en
ce
b
e
t
w
ee
n
t
h
e
m
ax
i
m
u
m
f
it
n
es
s
an
d
m
i
n
i
m
u
m
f
it
n
es
s
i
s
ze
r
o
,
th
e
s
o
l
u
tio
n
i
s
s
a
id
to
b
e
co
n
v
er
g
ed
a
n
d
th
e
s
i
m
u
latio
n
w
i
ll
s
to
p
.
T
h
e
v
al
u
e
o
f
ac
c
u
r
ac
y
w
as
s
et
to
0
.
0
0
0
1
as
s
h
o
w
n
i
n
t
h
e
E
q
u
atio
n
(
4
)
:
(
4
)
w
h
er
e
f
m
ax
i
s
m
a
x
i
m
u
m
e
n
e
r
g
y
g
en
er
ate
f
r
o
m
n
e
w
p
ar
en
t
‟
s
p
o
p
u
latio
n
a
n
d
f
m
i
n
is
t
h
e
m
in
i
m
u
m
en
er
g
y
g
en
er
ate
f
r
o
m
th
e
s
a
m
e
p
o
p
u
latio
n
.
I
f
th
e
co
n
v
er
g
e
n
ce
test
f
ail,
th
e
n
e
w
p
ar
en
t
‟
s
p
o
p
u
latio
n
w
i
ll
r
ep
ea
t
th
e
s
a
m
e
p
r
o
ce
s
s
b
eg
i
n
n
in
g
at
m
u
tatio
n
p
h
ase
u
n
til it
‟
s
co
n
v
er
g
e.
2
.
4
.
B
uil
din
g
E
nerg
y
Si
m
u
la
t
o
r:
E
nerg
y
P
lus
T
o
p
er
f
o
r
m
th
e
b
u
ild
i
n
g
s
i
m
u
latio
n
,
a
b
u
ild
in
g
m
o
d
el
f
ile
i
n
I
DF
f
o
r
m
a
t
is
p
r
ep
ar
ed
w
it
h
w
ea
t
h
er
f
ile
f
o
r
s
ite
lo
ca
tio
n
.
An
I
DF
f
ile
co
n
s
is
t
s
o
f
a
b
u
ild
i
n
g
m
o
d
el
d
ata
s
u
c
h
a
s
b
u
ild
in
g
p
ar
a
m
eter
s
,
HV
AC
s
et
u
p
,
elec
tr
ical
eq
u
ip
m
e
n
t
etc.
I
DF
f
ile
also
co
n
tai
n
s
a
s
et
tin
g
f
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s
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m
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p
er
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d
an
d
tim
e
s
t
ep
w
h
ic
h
is
cr
u
c
ial
f
o
r
co
m
m
u
n
ica
tio
n
b
et
w
ee
n
s
i
m
u
lato
r
s
.
T
h
er
e
ar
e
t
w
o
w
a
y
s
to
g
e
n
er
ate
I
DF
f
ile,
w
h
ic
h
i
s
b
y
m
an
u
all
y
cr
ea
t
e
a
n
e
w
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ile
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r
m
o
d
if
ied
a
n
o
l
d
er
I
DF
f
ile
o
r
b
y
u
s
in
g
a
3
r
d
p
ar
ty
GUI
s
o
f
t
w
ar
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y
u
s
in
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t
h
e
3
r
d
p
ar
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o
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t
w
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ch
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ated
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ild
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g
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m
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latio
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s
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to
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ed
in
a
d
atab
ase.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
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d
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ed
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et
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m
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la
to
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e
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s
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d
ata
g
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er
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r
o
m
b
u
i
ld
in
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s
i
m
u
lat
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n
is
s
to
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ed
in
a
d
atab
ase.
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P
alg
o
r
ith
m
is
w
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itten
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d
ed
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tlab
en
v
ir
o
n
m
en
t
b
y
s
u
b
-
d
i
v
id
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n
g
in
to
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esp
ec
tiv
e
p
h
a
s
es
.
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h
e
p
r
o
ce
s
s
b
eg
in
s
i
n
in
it
ializ
atio
n
as
to
co
llect
2
0
in
itial
p
o
p
u
latio
n
s
“
p
ar
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ts
”
a
n
d
en
d
s
w
it
h
co
n
v
er
g
en
ce
test
as
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f
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n
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n
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m
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r
.
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e
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P
o
p
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m
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al
g
o
r
ith
m
i
s
u
s
ed
to
g
e
n
er
ate
a
v
ec
to
r
s
o
f
r
a
n
d
o
m
d
ec
is
io
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co
n
f
ig
u
r
atio
n
an
d
th
e
n
th
r
o
u
g
h
B
C
VT
B
,
co
u
p
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g
f
r
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m
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w
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tr
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s
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er
s
t
h
e
d
ata
to
B
E
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E
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er
g
y
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m
t
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,
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l
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s
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m
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l
ates
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ld
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m
o
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els
w
i
th
g
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co
n
f
i
g
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r
atio
n
a
n
d
te
s
t
i
t
f
o
r
a
p
er
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d
o
f
ti
m
e
an
d
r
ep
o
r
t
th
e
r
esp
o
n
s
e
e
n
er
g
y
co
n
s
u
m
p
tio
n
in
h
o
u
r
l
y
m
an
n
er
.
T
h
e
p
r
o
ce
s
s
w
il
l
s
to
p
at
t
h
e
en
d
o
f
th
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p
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r
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t
il
it
s
m
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ter
m
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n
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cr
i
ter
ia.
Fig
u
r
e
3
ab
o
v
e
(
r
ig
h
t)
s
h
o
w
s
th
e
o
v
er
all
f
lo
w
c
h
ar
t
f
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r
th
e
ca
lib
r
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n
p
r
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ce
s
s
.
2
.
6
.
B
uil
din
g
E
nerg
y
E
v
a
lua
t
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n
T
w
o
ev
al
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n
s
f
r
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m
I
P
MV
P
,
No
r
m
alize
d
Me
a
n
B
iased
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r
r
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r
(
NM
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d
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n
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o
f
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Me
an
Sq
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ar
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r
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)
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h
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s
co
n
s
id
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p
tim
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ll
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lib
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ated
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V(
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th
e
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P
MV
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.
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B
E
an
d
C
V(
R
M
SE)
E
q
u
atio
n
s
ar
e
p
r
o
v
id
ed
as
i
n
(
5
)
an
d
(
6
)
r
esp
ec
tiv
el
y
.
T
h
e
o
p
ti
m
ized
e
n
er
g
y
co
n
s
u
m
p
tio
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w
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th
th
e
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ig
h
t
v
ar
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les co
n
f
i
g
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r
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ll
ed
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lib
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ated
b
aselin
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m
o
d
el.
3.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
I
n
t
h
is
s
ec
tio
n
,
t
h
e
r
es
u
lts
o
f
th
e
p
r
o
p
o
s
ed
en
er
g
y
m
o
d
el
au
to
ca
lib
r
atio
n
ap
p
r
o
ac
h
u
s
i
n
g
to
m
at
o
g
r
ee
n
h
o
u
s
e
as
t
h
e
ca
s
e
s
t
u
d
y
is
p
r
esen
ted
.
A
s
in
g
le
o
b
j
ec
ti
v
e
f
u
n
ctio
n
w
h
ic
h
i
s
to
m
i
n
i
m
ize
er
r
o
r
i
n
h
o
u
r
l
y
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er
g
y
co
n
s
u
m
p
tio
n
i
s
u
s
ed
i
n
t
h
e
E
P
al
g
o
r
ith
m
.
T
h
e
m
ai
n
p
u
r
p
o
s
es
o
f
th
i
s
s
t
u
d
y
i
s
to
s
ea
r
ch
f
o
r
t
h
e
b
es
t
v
ar
iab
les
co
n
f
i
g
u
r
atio
n
f
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r
ca
lib
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er
g
y
m
o
d
el
t
h
at
lead
s
to
ac
ce
p
tab
le
NM
B
E
an
d
C
V(
R
SME
)
b
y
I
P
MV
P
.
Fig
u
r
e
4
p
r
ese
n
ts
t
h
e
ac
t
u
al
d
ail
y
e
n
er
g
y
p
ater
n
t
h
at
o
b
ta
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ed
f
r
o
m
th
e
g
r
ee
n
h
o
u
s
e
an
d
u
s
ed
f
o
r
ca
lib
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n
to
co
m
p
ar
e
w
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th
t
h
e
s
i
m
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n
d
ata.
T
h
e
d
if
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et
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h
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d
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lated
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d
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Fig
u
r
e
5
s
h
o
w
s
t
h
e
ac
tu
al
u
s
a
g
e
o
f
th
e
eq
u
ip
m
e
n
t
p
er
h
o
u
r
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
A
u
to
ma
ted
C
a
lib
r
a
tio
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Of
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h
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[1
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.
Bu
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En
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y
S
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f
twa
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[
On
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n
e
].
A
v
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a
b
le:
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tt
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:/
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A
c
c
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ss
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d
:
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1
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.
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]
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[3
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“
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].
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[4
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y
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.
En
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rg
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ld
.
2
0
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l:
1
2
7
,
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5
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–
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6
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.
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M
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Da
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:
7
8
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p
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9
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1
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2
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7
6
.
[6
]
Ha
g
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F
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2
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:
4
5
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p
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[7
]
Na
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d
In
d
o
o
r
T
h
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rm
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l
Co
m
f
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rt
A
Ne
w
M
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th
o
d
Us
i
n
g
A
rti
f
i
c
ial
Be
e
Co
lo
n
y
(A
BC).
En
e
rg
y
a
n
d
Bu
il
d
in
g
s
.
2
0
1
6
.
Iss
u
e
:
1
3
1
,
p
a
g
e
s: 4
2
-
5
3
.
[8
]
T
.
Ho
n
g
,
J.
Kim
,
J.
Je
o
n
g
,
M
.
L
e
e
,
a
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d
C
.
Ji.
A
u
to
m
a
ti
c
c
a
li
b
ra
ti
o
n
m
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d
e
l
o
f
a
b
u
il
d
in
g
e
n
e
rg
y
sim
u
latio
n
u
si
n
g
opt
im
iza
ti
o
n
a
lg
o
rit
h
m
.
En
e
rg
y
P
ro
c
e
d
ia
.
2
0
1
7
.
V
o
l
:
1
0
5
,
p
a
g
e
s: 3
6
9
8
–
3
7
0
4
.
[9
]
T
.
Ya
n
g
,
Y.
P
a
n
,
J.
M
a
o
,
Y.
W
a
n
g
,
a
n
d
Z.
Hu
a
n
g
.
A
n
a
u
to
m
a
t
e
d
o
p
ti
m
iza
ti
o
n
m
e
th
o
d
f
o
r
c
a
li
b
ra
ti
n
g
b
u
il
d
i
n
g
e
n
e
rg
y
si
m
u
latio
n
m
o
d
e
ls
w
it
h
m
e
a
su
re
d
d
a
ta:
Orie
n
tatio
n
a
n
d
a
c
a
se
stu
d
y
.
Ap
p
l.
En
e
rg
y
.
2
0
1
6
.
V
o
l
:
1
7
9
,
p
a
g
e
s:
1
2
2
0
–
1
2
3
1
.
[1
0
]
W
e
tt
e
r,
M
.
Co
-
S
im
u
latio
n
o
f
Bu
il
d
in
g
E
n
e
rg
y
a
n
d
Co
n
tr
o
l
S
y
ste
m
s
w
it
h
th
e
Bu
il
d
in
g
Co
n
tro
ls
Virtu
a
l
T
e
st
Be
d
.
J
o
u
rn
a
l
o
f
B
u
il
d
i
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Per
fo
rm
a
n
c
e
S
imu
l
a
ti
o
n
.
2
0
1
1
.
V
o
l
:
4
(
3
),
p
a
g
e
s: 1
8
5
-
2
0
3
.
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