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K
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q
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Hy
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ac
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lear
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T
h
is i
s
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n
o
p
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c
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ss
a
rticle
u
n
d
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r th
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CC B
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SA
li
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se
.
C
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r
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p
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A
uth
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Hid
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Sib
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Dep
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tm
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f
I
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Facu
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Scien
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Un
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Al
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Qu
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5
6
3
5
1
W
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C
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J
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I
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s
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iq
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ac
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id
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I
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D
UCT
I
O
N
C
lim
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ch
an
g
e
h
ar
m
s
h
u
m
a
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life
.
On
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o
f
th
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im
p
ac
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lo
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war
m
in
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in
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k
n
o
wn
as
th
e
Ur
b
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Hea
t
I
s
lan
d
(
UHI
)
[
1
]
.
Ho
t
a
r
ea
s
will
ex
p
o
s
e
b
u
i
ld
in
g
s
to
h
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air
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air
q
u
ali
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id
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b
u
ild
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g
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ec
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T
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f
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s
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o
o
d
air
q
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ality
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n
s
id
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in
g
s
[
2
]
.
T
h
e
q
u
ality
o
f
air
is
cr
u
cial
f
o
r
t
h
e
h
ea
lth
o
f
t
h
e
I
s
lam
ic
b
o
a
r
d
in
g
s
ch
o
o
l
r
esid
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ts
.
Op
tim
al
air
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ality
p
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s
itiv
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f
lu
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ce
s
h
ea
lth
,
wh
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s
s
u
b
p
ar
air
q
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ality
ad
v
er
s
ely
af
f
ec
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well
-
b
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d
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ce
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is
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f
o
r
t
am
o
n
g
r
esid
en
ts
in
d
o
o
r
s
[
3
]
,
[
4
]
.
I
n
d
o
o
r
air
q
u
ali
ty
is
clo
s
ely
r
elate
d
to
th
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m
al
co
m
f
o
r
t
v
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iab
les.
Po
o
r
air
h
u
m
id
ity
is
o
n
e
o
f
t
h
e
th
er
m
al
v
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r
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th
at
ca
u
s
es
p
o
o
r
air
q
u
ality
,
ca
u
s
in
g
h
ea
lth
p
r
o
b
lem
s
[
5
]
.
Po
o
r
air
q
u
ality
will
also
ca
u
s
e
a
d
ec
r
ea
s
e
in
h
u
m
an
p
er
f
o
r
m
an
ce
at
wo
r
k
[
6
]
.
I
n
d
o
o
r
air
q
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ality
is
r
elate
d
to
b
u
ild
in
g
v
en
tilatio
n
.
Natu
r
al
v
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tilatio
n
is
o
n
e
way
to
m
ai
n
tain
g
o
o
d
air
q
u
ality
[
7
]
.
Na
tu
r
al
v
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tilatio
n
is
co
n
s
id
er
ed
a
s
im
p
le
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n
d
ef
f
ec
tiv
e
m
eth
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d
o
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c
h
an
g
e.
Occ
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ts
h
a
v
e
a
m
ajo
r
in
f
lu
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ce
o
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th
e
ef
f
ec
tiv
en
ess
o
f
n
atu
r
al
v
en
ti
latio
n
[
8
]
.
Natu
r
al
v
en
tilatio
n
d
esig
n
s
tr
ateg
ies
ar
e
o
n
e
wa
y
to
cr
ea
te
en
er
g
y
Evaluation Warning : The document was created with Spire.PDF for Python.
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J
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3
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Sep
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20
25
:
1
7
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1796
ef
f
icien
cy
[
9
]
.
Air
s
p
ee
d
th
r
o
u
g
h
v
en
tilatio
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is
o
n
e
asp
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th
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a
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to
th
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in
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ea
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ai
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tem
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r
e
[
1
0
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.
E
n
er
g
y
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f
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ca
n
b
e
ac
h
iev
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d
b
y
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s
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[
1
1
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E
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[
1
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I
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r
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itectu
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p
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n
iq
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d
e
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er
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[
1
3
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.
T
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y
th
e
r
m
al
co
m
f
o
r
t
o
r
th
e
air
tem
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er
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r
e
with
in
th
e
I
s
lam
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ar
d
in
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s
ch
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l.
Air
q
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ality
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d
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cr
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o
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esid
en
ts
’
in
d
o
o
r
ac
tiv
ities
.
Mo
r
eo
v
er
,
th
er
m
al
co
m
f
o
r
t
ca
n
f
ac
ilit
ate
th
e
co
n
s
tr
u
ctio
n
o
f
e
n
er
g
y
-
ef
f
icien
t
ed
if
ices,
th
er
eb
y
m
itig
atin
g
e
n
er
g
y
wa
s
te
[
1
4
]
,
[
1
5
]
.
E
n
er
g
y
in
e
f
f
ic
i
en
cy
f
r
eq
u
e
n
tly
tr
a
n
s
p
ir
es
in
en
v
ir
o
n
m
en
ts
wh
er
e
air
q
u
ality
an
d
th
er
m
al
c
o
m
f
o
r
t a
r
e
s
u
b
o
p
tim
al
[
1
6
]
.
T
h
e
d
is
tin
ct
n
atu
r
al
c
o
n
d
itio
n
s
o
f
h
ig
h
la
n
d
s
an
d
lo
wlan
d
s
ca
n
in
f
l
u
en
ce
air
q
u
ality
a
n
d
th
e
r
m
al
co
m
f
o
r
t.
Hig
h
lan
d
s
ty
p
ically
ex
h
ib
it
lo
wer
tem
p
e
r
atu
r
es
an
d
r
ed
u
ce
d
air
d
en
s
ity
,
wh
er
ea
s
lo
wlan
d
s
g
en
er
ally
ex
p
er
ien
ce
elev
ated
tem
p
er
atu
r
es
an
d
in
cr
ea
s
ed
h
u
m
i
d
ity
[
1
7
]
.
T
o
en
h
an
ce
air
q
u
ality
an
d
th
er
m
al
co
m
f
o
r
t
in
I
s
lam
ic
b
o
ar
d
in
g
s
ch
o
o
ls
s
itu
ated
in
h
ig
h
la
n
d
an
d
lo
wlan
d
r
eg
io
n
s
,
a
s
u
p
er
v
is
ed
lear
n
in
g
m
o
d
e
l
m
ay
b
e
em
p
lo
y
ed
[
1
8
]
.
Su
p
er
v
is
ed
le
ar
n
in
g
is
a
m
ac
h
in
e
lear
n
in
g
t
ec
h
n
iq
u
e
u
tili
ze
d
t
o
a
n
aly
ze
d
ata
an
d
p
r
e
d
ict
air
q
u
ality
an
d
th
er
m
al
co
m
f
o
r
t
in
I
s
lam
ic
b
o
ar
d
in
g
s
ch
o
o
ls
[
1
9
]
,
[
2
0
]
.
Alg
o
r
ith
m
s
en
c
o
m
p
ass
ed
with
in
th
e
s
u
p
er
v
is
ed
lear
n
in
g
p
a
r
ad
ig
m
in
cl
u
d
e
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
e
(
SVM)
,
K
-
n
ea
r
est
n
ei
g
h
b
o
r
(
KNN)
,
am
o
n
g
o
th
er
s
[
2
1
]
,
[
2
2
]
.
T
ab
le
1
r
ev
ea
ls
t
h
at
s
tu
d
ies
h
a
v
e
b
ee
n
u
n
d
er
ta
k
en
to
p
r
ed
ict
th
er
m
al
co
m
f
o
r
t
an
d
air
q
u
alit
y
u
tili
zin
g
m
ac
h
in
e
lear
n
in
g
m
o
d
els
with
d
iv
er
s
e
s
u
p
e
r
v
is
ed
lear
n
in
g
a
lg
o
r
ith
m
s
.
No
n
eth
eless
,
n
o
p
r
ev
io
u
s
r
esear
ch
h
as
in
teg
r
ated
t
h
er
m
al
c
o
m
f
o
r
t
with
air
q
u
ality
f
o
r
ec
asti
n
g
.
Mo
r
eo
v
er
,
n
u
m
er
o
u
s
s
tu
d
i
es
h
av
e
i
d
en
tifie
d
alg
o
r
ith
m
s
with
o
p
tim
al
ac
cu
r
ac
y
,
s
u
ch
as
SVM
an
d
KN
N.
T
h
is
r
esear
ch
in
teg
r
ates
th
ese
two
alg
o
r
ith
m
s
to
cr
ea
te
an
o
p
tim
al
h
y
b
r
id
m
o
d
e
l f
o
r
p
r
ed
ictin
g
th
e
r
m
al
co
m
f
o
r
t a
n
d
air
q
u
ality
.
T
ab
le
1
.
L
iter
atu
r
e
r
ev
iew
A
u
t
h
o
r
n
u
m
b
e
r
R
e
v
i
e
w
i
n
g
r
e
su
l
t
s
[
4
]
Th
i
s
r
e
se
a
r
c
h
f
o
r
mu
l
a
t
e
s
a
p
r
e
d
i
c
t
i
o
n
mo
d
e
l
f
o
r
i
n
d
o
o
r
P
M
1
0
c
o
n
c
e
n
t
r
a
t
i
o
n
s u
s
i
n
g
m
u
l
t
i
p
l
e
l
i
n
e
a
r
r
e
g
r
e
ss
i
o
n
a
n
a
l
y
ses
,
f
o
c
u
s
i
n
g
o
n
e
l
e
me
n
t
a
r
y
s
c
h
o
o
l
s
,
k
i
n
d
e
r
g
a
r
t
e
n
s
,
a
n
d
d
a
y
c
a
r
e
c
e
n
t
e
r
s i
n
S
e
o
u
l
,
S
o
u
t
h
K
o
r
e
a
.
T
h
e
f
i
n
d
i
n
g
s
i
n
d
i
c
a
t
e
t
h
a
t
d
a
y
c
a
r
e
c
e
n
t
e
r
s
e
x
h
i
b
i
t
t
h
e
h
i
g
h
e
st
c
o
n
c
e
n
t
r
a
t
i
o
n
s.
[
2
3
]
Th
i
s
r
e
se
a
r
c
h
e
x
a
mi
n
e
s
i
n
d
o
o
r
a
i
r
q
u
a
l
i
t
y
s
t
u
d
i
e
s
a
c
r
o
ss
v
a
r
i
o
u
s
c
o
u
n
t
r
i
e
s,
u
t
i
l
i
z
i
n
g
v
a
r
i
a
b
l
e
s s
u
c
h
a
s
v
o
l
a
t
i
l
e
o
r
g
a
n
i
c
c
o
mp
o
u
n
d
s (V
O
C
s)
,
p
a
r
t
i
c
u
l
a
t
e
m
a
t
t
e
r
(
P
M
)
,
a
n
d
c
a
r
b
o
n
d
i
o
x
i
d
e
(
C
O
2
)
.
Th
e
r
e
s
u
l
t
s s
h
o
w
t
h
a
t
i
n
c
r
e
a
s
i
n
g
a
i
r
f
l
o
w
c
a
n
r
e
d
u
c
e
a
l
a
r
mi
n
g
l
y
e
l
e
v
a
t
e
d
p
o
l
l
u
t
a
n
t
c
o
n
c
e
n
t
r
a
t
i
o
n
s.
[
2
4
]
Th
i
s
r
e
se
a
r
c
h
e
mp
l
o
y
s
t
h
e
S
V
M
a
l
g
o
r
i
t
h
m
i
n
ma
c
h
i
n
e
l
e
a
r
n
i
n
g
t
o
p
r
e
d
i
c
t
p
o
l
l
u
t
a
n
t
l
e
v
e
l
s
,
p
a
r
t
i
c
u
l
a
t
e
m
e
t
t
e
r
,
a
n
d
t
h
e
a
i
r
q
u
a
l
i
t
y
i
n
d
e
x
.
T
h
e
c
l
a
ssi
f
i
c
a
t
i
o
n
u
t
i
l
i
z
e
d
s
i
x
a
i
r
q
u
a
l
i
t
y
c
a
t
e
g
o
r
i
e
s
,
a
t
t
a
i
n
i
n
g
a
n
a
c
c
u
r
a
c
y
o
f
9
4
.
1
%
.
[
2
5
]
Th
i
s
r
e
se
a
r
c
h
p
r
e
se
n
t
s a
n
e
n
e
r
g
y
-
e
f
f
i
c
i
e
n
t
t
h
e
r
ma
l
c
o
mf
o
r
t
m
o
d
e
l
u
t
i
l
i
z
i
n
g
a
mac
h
i
n
e
l
e
a
r
n
i
n
g
me
t
h
o
d
o
l
o
g
y
.
Th
e
si
m
u
l
a
t
i
o
n
r
e
su
l
t
s
i
n
d
i
c
a
t
e
t
h
a
t
t
h
e
S
V
M
a
l
g
o
r
i
t
h
m
su
r
p
a
ss
e
s
o
t
h
e
r
a
l
g
o
r
i
t
h
ms.
[
2
6
]
Th
i
s
st
u
d
y
se
e
k
s
t
o
f
o
r
e
c
a
st
t
h
e
r
ma
l
c
o
mf
o
r
t
u
t
i
l
i
z
i
n
g
d
a
t
a
t
h
r
o
u
g
h
t
h
e
S
V
M
a
l
g
o
r
i
t
h
m
a
n
d
v
a
r
i
o
u
s
o
t
h
e
r
mac
h
i
n
e
l
e
a
r
n
i
n
g
a
l
g
o
r
i
t
h
ms
.
I
n
c
o
m
p
a
r
i
so
n
t
o
o
t
h
e
r
a
l
g
o
r
i
t
h
ms,
t
h
e
r
e
s
u
l
t
s
sh
o
w
t
h
a
t
S
V
M
ma
k
e
s
t
h
e
r
m
a
l
c
o
mf
o
r
t
p
r
e
d
i
c
t
i
o
n
s
mu
c
h
mo
r
e
a
c
c
u
r
a
t
e
.
[
2
7
]
Th
i
s
st
u
d
y
c
o
n
s
t
r
u
c
t
e
d
a
t
h
e
r
ma
l
c
o
m
f
o
r
t
m
o
d
e
l
u
t
i
l
i
z
i
n
g
t
h
e
K
N
N
me
t
h
o
d
t
o
e
st
a
b
l
i
s
h
a
d
a
p
t
i
v
e
c
o
mf
o
r
t
f
o
r
p
a
ss
e
n
g
e
r
s
.
W
e
e
v
a
l
u
a
t
e
d
t
h
e
K
N
N
-
b
a
se
d
t
h
e
r
m
a
l
c
o
mf
o
r
t
m
o
d
e
l
u
s
i
n
g
1
,
0
0
0
d
a
t
a
se
t
s a
n
d
a
c
h
i
e
v
e
d
a
r
e
l
a
t
i
v
e
l
y
h
i
g
h
a
c
c
u
r
a
c
y
l
e
v
e
l
.
[
2
8
]
Th
i
s
r
e
se
a
r
c
h
a
i
ms
t
o
f
o
r
e
c
a
s
t
t
h
e
a
i
r
q
u
a
l
i
t
y
i
n
d
e
x
u
t
i
l
i
z
i
n
g
A
N
N
a
n
d
K
N
N
a
l
g
o
r
i
t
h
ms.
T
h
e
c
o
n
c
l
u
si
o
n
i
n
d
i
c
a
t
e
s
t
h
a
t
t
h
e
K
N
N
a
l
g
o
r
i
t
h
m
a
t
t
a
i
n
e
d
t
h
e
h
i
g
h
e
st
a
c
c
u
r
a
c
y
.
[
2
9
]
Th
i
s
r
e
se
a
r
c
h
i
n
t
r
o
d
u
c
e
s
a
t
h
e
r
ma
l
c
o
mf
o
r
t
m
o
n
i
t
o
r
i
n
g
s
y
st
e
m f
o
r
h
o
t
a
n
d
h
u
mi
d
c
l
i
ma
t
e
s
u
t
i
l
i
z
i
n
g
t
h
e
K
N
N
mo
d
e
l
.
T
h
e
f
i
n
d
i
n
g
s
i
n
d
i
c
a
t
e
t
h
a
t
t
h
e
mo
d
e
l
a
t
t
a
i
n
s a
sa
t
i
sf
a
c
t
o
r
y
a
c
c
u
r
a
c
y
sco
r
e
.
2.
M
E
T
H
O
D
T
h
is
r
esear
ch
em
p
lo
y
s
a
q
u
a
n
titativ
e
m
eth
o
d
o
lo
g
y
,
co
m
m
en
cin
g
with
th
e
d
elin
ea
tio
n
o
f
r
esear
ch
p
r
o
b
lem
s
a
n
d
o
b
jectiv
es,
wh
i
ch
h
as
b
ee
n
f
in
alize
d
,
s
u
cc
ee
d
ed
b
y
a
liter
atu
r
e
r
ev
iew
o
f
an
tece
d
en
t
s
tu
d
ies
p
er
tin
en
t
to
th
e
s
u
b
ject
m
atter
.
Data
co
llectio
n
s
u
r
v
e
y
s
an
d
p
er
m
is
s
io
n
s
will
b
e
ex
ec
u
t
ed
at
5
–
1
0
I
s
lam
ic
b
o
ar
d
in
g
s
ch
o
o
ls
in
b
o
th
h
ig
h
lan
d
an
d
lo
wlan
d
r
eg
io
n
s
,
with
W
o
n
o
s
o
b
o
,
C
en
tr
al
J
av
a,
ex
em
p
lify
i
n
g
th
e
h
ig
h
lan
d
s
a
n
d
Po
n
tian
ak
,
W
est
Kalim
an
tan
,
ex
em
p
li
f
y
in
g
th
e
lo
wlan
d
s
.
T
h
e
d
ata
co
llec
tio
n
in
W
o
n
o
s
o
b
o
will
en
co
m
p
ass
th
er
m
al
co
m
f
o
r
t
v
ar
iab
les,
in
clu
d
i
n
g
air
te
m
p
er
atu
r
e,
h
u
m
id
ity
,
win
d
s
p
ee
d
,
s
o
lar
r
ad
iatio
n
tem
p
er
atu
r
e,
ac
tiv
it
y
,
an
d
cl
o
th
in
g
,
m
ea
s
u
r
ed
with
i
n
s
tr
u
m
en
ts
s
u
ch
as
h
u
m
id
ity
m
et
er
s
,
s
o
lar
r
ad
iatio
n
s
en
s
o
r
s
,
an
d
a
n
em
o
m
eter
s
.
A
d
d
itio
n
ally
,
ai
r
q
u
ality
v
ar
ia
b
les,
s
p
ec
if
ically
C
O
2
,
PM1
0
,
PM2
.
5
,
an
d
PM1
.
0
,
will
b
e
ass
ess
ed
u
s
in
g
C
O
2
s
en
s
o
r
s
an
d
p
ar
ticle
co
u
n
ter
s
.
C
o
m
p
ar
ab
le
d
ata
will
b
e
g
at
h
er
ed
in
Po
n
tian
ak
u
tili
zin
g
th
e
s
am
e
in
s
tr
u
m
en
ts
.
A
m
in
im
u
m
o
f
2
,
0
0
0
d
ataset
s
will
b
e
g
ath
er
ed
f
r
o
m
ea
ch
lo
ca
tio
n
,
y
ield
in
g
a
to
tal
o
f
4
,
0
0
0
d
atasets
.
Fo
llo
win
g
d
ata
co
llectio
n
,
a
r
ec
a
p
an
d
p
r
ep
a
r
atio
n
o
f
th
e
d
ata
will
b
e
ex
ec
u
ted
f
o
r
th
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Op
timiz
in
g
s
u
p
ervis
ed
lea
r
n
in
g
mo
d
el
fo
r
th
erma
l c
o
mfo
r
t a
n
d
a
ir
q
u
a
lity
(
Hid
a
ya
t
u
s
S
ib
y
a
n
)
1797
d
ev
elo
p
m
e
n
t
o
f
s
u
p
er
v
is
ed
le
ar
n
in
g
m
o
d
els
u
tili
zin
g
t
h
e
S
VM
an
d
KNN
alg
o
r
it
h
m
s
,
im
p
lem
en
ted
i
n
Py
th
o
n
an
d
Go
o
g
le
C
o
lab
.
A
h
y
b
r
id
m
o
d
el
in
teg
r
ati
n
g
th
ese
alg
o
r
ith
m
s
will
b
e
d
ev
elo
p
e
d
an
d
o
p
tim
ized
to
attain
o
p
tim
al
p
r
ed
ictio
n
s
f
o
r
air
q
u
a
lity
an
d
th
er
m
al
co
m
f
o
r
t.
T
h
er
m
al
co
m
f
o
r
t
an
d
air
q
u
al
ity
in
I
s
lam
ic
b
o
ar
d
i
n
g
s
ch
o
o
ls
lo
ca
ted
in
h
ig
h
lan
d
an
d
lo
w
lan
d
ar
ea
s
n
ee
d
o
p
tim
izatio
n
.
Data
co
lle
ctio
n
will
in
v
o
lv
e
m
ea
s
u
r
in
g
th
er
m
al
co
m
f
o
r
t
an
d
in
d
o
o
r
a
ir
q
u
ality
v
ar
iab
les.
R
esear
ch
d
ata
will
b
e
co
llect
ed
f
r
o
m
s
ev
er
al
I
s
lam
ic
b
o
a
r
d
in
g
s
ch
o
o
ls
in
W
o
n
o
s
o
b
o
,
r
e
p
r
esen
tin
g
h
ig
h
lan
d
ar
ea
s
,
an
d
Po
n
tian
a
k
,
r
e
p
r
ese
n
tin
g
lo
wlan
d
ar
ea
s
,
with
2
,
0
0
0
d
atasets
ea
ch
,
r
esu
ltin
g
in
a
to
tal
o
f
4
,
0
0
0
d
atasets
.
Pre
v
io
u
s
s
tu
d
ies
h
av
e
s
h
o
wn
th
at
m
ac
h
in
e
lear
n
in
g
ap
p
r
o
ac
h
es
ca
n
p
r
e
d
ict
o
u
tc
o
m
es
b
ased
o
n
d
ata
p
atter
n
s
[
1
8
]
.
Ma
ch
in
e
lear
n
in
g
m
o
d
els
ca
n
also
f
o
r
ec
as
t
th
er
m
al
co
m
f
o
r
t
an
d
air
q
u
ality
[
1
7
]
.
So
m
e
s
tu
d
ies
h
av
e
d
em
o
n
s
tr
ated
th
at
s
u
p
e
r
v
is
ed
lear
n
in
g
alg
o
r
ith
m
s
,
s
u
ch
as
SVM
an
d
KNN,
ac
h
i
ev
e
h
ig
h
ac
c
u
r
ac
y
lev
els
[
2
9
]
.
Ho
wev
er
,
th
ese
t
wo
alg
o
r
ith
m
s
h
av
e
n
o
t
y
et
b
ee
n
u
s
ed
to
g
eth
er
to
p
r
ed
ict
b
o
th
air
q
u
ali
ty
an
d
th
er
m
al
co
m
f
o
r
t.
T
h
e
o
b
jectiv
e
o
f
th
is
r
esear
ch
is
to
d
ev
elo
p
a
h
y
b
r
id
s
u
p
er
v
is
ed
m
ac
h
in
e
lear
n
i
n
g
m
o
d
el
u
s
in
g
th
e
SVM
an
d
KNN
alg
o
r
ith
m
s
.
B
y
co
m
b
in
i
n
g
th
ese
two
alg
o
r
ith
m
s
,
an
o
p
tim
al
m
o
d
el
is
ex
p
ec
ted
to
p
r
ed
ict
air
q
u
ality
an
d
th
er
m
al
c
o
m
f
o
r
t.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
Resea
rc
h da
t
a
des
cr
ipti
o
ns
I
s
lam
ic
b
o
ar
d
i
n
g
s
ch
o
o
ls
we
r
e
s
itu
ated
in
two
s
ep
ar
ate
lo
ca
tio
n
s
:
W
o
n
o
s
o
b
o
,
d
e
n
o
tin
g
h
ig
h
lan
d
ar
ea
s
,
an
d
Po
n
tian
ak
,
d
en
o
tin
g
lo
wlan
d
ar
ea
s
.
A
cu
m
u
lativ
e
to
tal
o
f
4
,
0
0
0
d
atasets
was
a
m
ass
ed
,
co
m
p
r
is
in
g
2
,
0
0
0
d
atasets
f
r
o
m
ea
c
h
s
ite.
T
h
e
ass
ess
ed
v
ar
iab
les
en
co
m
p
ass
ed
air
tem
p
er
atu
r
e,
h
u
m
id
ity
,
win
d
v
elo
city
,
an
d
s
o
lar
r
ad
iatio
n
f
o
r
th
er
m
a
l
co
m
f
o
r
t,
in
a
d
d
itio
n
to
C
O
2
,
PM1
0
,
PM2
.
5
,
an
d
PM1
.
0
c
o
n
ce
n
tr
atio
n
s
f
o
r
air
q
u
ality
.
T
h
e
d
atasets
wer
e
ex
am
in
ed
em
p
lo
y
in
g
s
u
p
er
v
is
ed
lear
n
in
g
m
o
d
els
to
f
o
r
ec
ast
air
q
u
ality
an
d
th
er
m
al
co
m
f
o
r
t.
C
lass
if
icati
o
n
was
co
n
d
u
cted
ac
c
o
r
d
in
g
to
th
e
ec
o
lo
g
ical
attr
ib
u
tes
o
f
th
e
two
ar
ea
s
.
Hig
h
lan
d
r
eg
io
n
s
ty
p
ically
d
em
o
n
s
tr
ated
r
e
d
u
ce
d
tem
p
e
r
a
tu
r
es
an
d
h
u
m
id
ity
r
elat
iv
e
t
o
lo
wlan
d
r
eg
i
o
n
s
,
wh
ich
u
s
u
ally
ex
p
er
ien
ce
d
elev
ated
tem
p
er
atu
r
es a
n
d
h
u
m
id
ity
lev
els.
3
.
1
.
1
.
T
em
pera
t
ure
d
is
t
ribut
io
n
Me
asu
r
em
en
ts
in
d
icate
d
th
at
air
tem
p
er
at
u
r
es
in
W
o
n
o
s
o
b
o
h
a
d
a
l
o
wer
d
is
tr
ib
u
tio
n
,
av
er
ag
in
g
ap
p
r
o
x
im
ately
2
5
°C
,
wh
er
e
as
Po
n
tian
a
k
d
is
p
lay
ed
h
ig
h
er
tem
p
e
r
atu
r
es,
a
v
er
ag
in
g
a
r
o
u
n
d
3
1
°C
.
T
h
is
illu
s
tr
ates
th
e
clim
atic
d
is
p
ar
i
ties
b
etwe
en
h
ig
h
lan
d
a
n
d
lo
wlan
d
r
eg
io
n
s
,
with
lo
wlan
d
s
ty
p
ically
ex
h
i
b
itin
g
war
m
er
tem
p
er
atu
r
es.
Fig
u
r
e
1
d
ep
icts
th
e
air
tem
p
er
atu
r
e
d
is
tr
ib
u
tio
n
in
b
o
th
lo
ca
t
io
n
s
.
3
.
1
.
2
.
T
he
a
ir
hu
m
idi
t
y
dis
t
ributio
ns
T
h
e
air
h
u
m
id
ity
d
if
f
er
s
f
r
o
m
th
e
two
r
esear
ch
s
ites
.
W
o
n
o
s
o
b
o
h
ad
lo
wer
h
u
m
id
ity
th
an
Po
n
tian
ak
.
Fig
u
r
e
2
s
h
o
ws th
e
air
h
u
m
id
it
y
d
is
tr
ib
u
tio
n
g
r
ap
h
ics o
f
b
o
th
lo
ca
tio
n
s
.
Fig
u
r
e
1
.
T
h
e
air
tem
p
e
r
atu
r
e
d
is
tr
ib
u
tio
n
s
in
W
o
n
o
s
o
b
o
an
d
Po
n
tian
a
k
Fig
u
r
e
2
.
T
h
e
air
h
u
m
id
ity
d
is
tr
ib
u
tio
n
s
in
W
o
n
o
s
o
b
o
an
d
Po
n
tian
a
k
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
9
,
No
.
3
,
Sep
tem
b
er
20
25
:
1
7
9
5
-
1
8
0
6
1798
3
.
1
.
3
.
T
he
d
is
t
rib
utio
n o
f
CO
2
T
h
e
C
O
2
co
n
ce
n
tr
atio
n
m
ea
s
u
r
em
en
t
is
u
s
ef
u
l
to
ass
ess
t
h
e
air
q
u
ality
at
t
h
e
I
s
lam
ic
b
o
ar
d
i
n
g
s
ch
o
o
ls
.
T
h
e
r
esu
lts
s
h
o
w
th
e
C
O
2
co
n
ce
n
tr
atio
n
in
W
o
n
o
s
o
b
o
is
h
ig
h
e
r
th
an
Po
n
tian
a
k
.
Fig
u
r
e
3
v
is
u
alize
s
th
e
C
O
2
co
n
ce
n
tr
atio
n
d
is
tr
ib
u
tio
n
s
f
r
o
m
b
o
th
lo
ca
tio
n
s
.
3
.
1
.
4
.
T
he
d
is
t
rib
utio
n o
f
P
M
2
.
5
T
h
e
m
ea
s
u
r
ed
PM2
.
5
p
ar
tic
le
co
n
ce
n
tr
atio
n
s
in
d
icate
d
t
h
at
W
o
n
o
s
o
b
o
ex
p
e
r
ien
ce
d
h
ig
h
er
air
p
o
llu
tio
n
lev
els
c
o
m
p
ar
e
d
to
Po
n
tian
ak
.
W
o
n
o
s
o
b
o
h
ad
a
n
av
er
ag
e
PM2
.
5
co
n
ce
n
t
r
atio
n
o
f
2
5
µg
/m
³,
wh
ile
Po
n
tian
ak
h
ad
a
lo
wer
av
e
r
ag
e
o
f
ab
o
u
t
1
5
µ
g
/m
³.
Fig
u
r
e
4
illu
s
tr
ates
th
e
PM2
.
5
d
is
tr
ib
u
tio
n
ac
r
o
s
s
th
e
two
lo
ca
tio
n
s
.
Fig
u
r
e
3
.
C
O
2
d
is
tr
ib
u
tio
n
s
in
W
o
n
o
s
o
b
o
an
d
Po
n
tian
ak
Fig
u
r
e
4
.
T
h
e
PM
2
.
5
d
is
tr
ib
u
t
io
n
s
in
W
o
n
o
s
o
b
o
an
d
Po
n
tian
ak
3
.
2
.
SVM
a
lg
o
rit
hm
ev
a
lua
t
io
n
I
n
th
is
s
tu
d
y
,
t
h
e
SVM
alg
o
r
i
th
m
is
ap
p
lied
to
p
r
e
d
icts
th
e
air
q
u
ality
a
n
d
tem
p
er
atu
r
e
c
o
m
f
o
r
t
in
I
s
lam
ic
b
o
ar
d
in
g
s
ch
o
o
ls
in
b
o
th
h
ig
h
lan
d
a
n
d
l
o
wlan
d
ar
ea
s
.
T
h
e
m
o
d
el
’
s
p
er
f
o
r
m
a
n
ce
u
s
in
g
k
ey
e
v
alu
atio
n
m
etr
ics
s
u
ch
as
r
ec
all,
ac
cu
r
ac
y
,
an
d
F1
-
s
co
r
e.
A
c
o
n
f
u
s
io
n
m
atr
ix
was u
s
ed
to
s
h
o
w
th
e
p
r
ed
ictio
n
s
.
T
h
e
SVM
m
o
d
el
was
tr
ain
ed
on
wea
th
er
-
r
elate
d
d
ata
co
llected
f
r
o
m
th
e
b
o
ar
d
i
n
g
s
ch
o
o
ls
,
in
clu
d
in
g
air
tem
p
er
atu
r
e,
h
u
m
id
ity
,
C
O
2
co
n
ce
n
tr
atio
n
,
a
n
d
lev
els
o
f
PM2
.
5
,
PM1
0
,
an
d
PM1
.
0
.
T
h
e
t
h
er
m
al
s
en
s
atio
n
v
o
te
(
T
SV)
,
wh
ich
is
a
lis
t
o
f
ty
p
es
o
f
th
er
m
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ated
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ased
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3
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e
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m
a
n
ce
f
r
o
m
4
0
%
to
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0
%
[
3
1
]
.
Ad
d
itio
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ally
,
r
esear
ch
o
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u
p
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t
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e
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t
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as
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h
iev
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3
%
an
d
R
F
r
ea
c
h
i
n
g
8
9
.
3
%
[
3
3
]
,
f
u
r
t
h
er
s
u
p
p
o
r
tin
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th
e
n
o
tio
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o
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ies
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[
3
4
]
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to
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ated
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o
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tim
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(
9
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%
ac
cu
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)
[
3
5
]
,
th
is
s
tu
d
y
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n
tr
o
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ce
s
a
h
y
b
r
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atter
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ch
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if
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r
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p
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ical
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n
d
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s
,
wh
i
ch
h
as
n
o
t
b
ee
n
ex
p
licitly
ex
p
lo
r
ed
in
p
r
ev
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u
s
r
esear
ch
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o
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g
h
th
is
s
tu
d
y
h
as
d
em
o
n
s
tr
ated
th
e
ef
f
ec
tiv
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ess
o
f
th
e
h
y
b
r
id
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SVM
m
o
d
el
in
p
r
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air
q
u
ality
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n
d
th
e
r
m
al
co
m
f
o
r
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in
I
s
lam
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d
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p
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tu
r
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ex
p
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d
ee
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g
m
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lik
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C
NN
o
r
R
NN
to
e
n
h
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ce
p
r
e
d
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ac
c
u
r
ac
y
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x
p
an
d
in
g
th
e
d
ataset
ac
r
o
s
s
d
iv
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e
clim
at
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im
p
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m
o
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el
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n
er
aliza
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I
n
teg
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r
ea
l
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ti
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I
o
T
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en
s
o
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d
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n
am
ic
air
q
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ality
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d
en
er
g
y
o
p
tim
izatio
n
.
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d
itio
n
ally
,
in
v
esti
g
atin
g
t
h
e
s
o
cio
-
ec
o
n
o
m
ic
im
p
ac
ts
o
f
p
r
ed
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m
o
d
e
ls
o
n
en
er
g
y
e
f
f
icien
cy
a
n
d
s
tu
d
en
t
well
-
b
ein
g
wo
u
ld
p
r
o
v
id
e
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m
o
r
e
co
m
p
r
eh
e
n
s
iv
e
p
er
s
p
ec
tiv
e
o
n
s
u
s
tain
ab
le
m
an
ag
em
en
t
o
f
I
s
lam
ic
b
o
ar
d
in
g
s
ch
o
o
ls
.
T
h
is
s
tu
d
y
d
em
o
n
s
tr
ates
th
e
e
f
f
ec
tiv
e
n
ess
o
f
m
ac
h
in
e
lea
r
n
i
n
g
in
p
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ed
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g
th
e
r
m
al
co
m
f
o
r
t
an
d
air
q
u
ality
in
I
s
lam
ic
b
o
ar
d
in
g
s
ch
o
o
ls
.
T
h
e
h
y
b
r
id
KNN
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SVM
m
o
d
el
ac
h
ie
v
ed
th
e
h
ig
h
est
a
cc
u
r
ac
y
,
o
f
f
er
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n
g
a
p
r
ac
tical
ap
p
r
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h
to
o
p
tim
iz
in
g
en
v
ir
o
n
m
en
tal
co
n
d
itio
n
s
.
T
h
ese
f
in
d
in
g
s
lay
th
e
g
r
o
u
n
d
w
o
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k
f
o
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f
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tu
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d
ap
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els t
o
en
h
a
n
ce
air
q
u
ality
,
en
er
g
y
e
f
f
icien
cy
,
a
n
d
s
tu
d
en
t w
ell
-
b
ein
g
.
4.
CO
NCLU
SI
O
N
T
h
is
r
esear
ch
h
ig
h
lig
h
ts
th
e
s
ig
n
if
ican
ce
o
f
p
r
ed
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e
m
o
d
els
in
o
p
tim
izin
g
th
e
r
m
al
c
o
m
f
o
r
t,
ai
r
q
u
ality
,
a
n
d
en
er
g
y
ef
f
icie
n
cy
in
I
s
lam
ic
b
o
ar
d
in
g
s
ch
o
o
ls
with
d
iv
er
s
e
g
eo
g
r
a
p
h
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co
n
d
itio
n
s
.
A
co
m
p
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is
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b
etwe
en
SVM
an
d
KNN
r
ev
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ls
th
at
K
NN
s
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p
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in
ter
m
s
o
f
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ac
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,
p
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io
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,
r
ec
all,
an
d
F1
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s
co
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e
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T
h
e
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n
teg
r
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o
f
b
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m
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in
to
a
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id
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p
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p
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ac
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o
f
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in
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a
b
alan
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d
s
o
lu
tio
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.
T
h
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f
in
d
i
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g
s
em
p
h
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th
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p
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ten
tial
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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d
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Vo
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3
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3
,
Sep
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b
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20
25
:
1
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1804
AUTHO
R
CO
NT
RI
B
UT
I
O
NS ST
A
T
E
M
E
N
T
T
h
is
jo
u
r
n
al
u
s
es
th
e
C
o
n
tr
ib
u
to
r
R
o
les
T
ax
o
n
o
m
y
(
C
R
ed
iT)
to
r
ec
o
g
n
ize
in
d
iv
id
u
al
au
th
o
r
co
n
tr
ib
u
tio
n
s
,
r
ed
u
ce
au
th
o
r
s
h
ip
d
is
p
u
tes,
an
d
f
ac
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ate
co
llab
o
r
atio
n
Na
m
e
o
f
Aut
ho
r
C
M
S
o
Va
F
o
I
R
D
O
E
Vi
S
u
P
F
u
Hid
ay
atu
s
Sib
y
an
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Her
m
awa
n
✓
✓
✓
✓
✓
✓
✓
E
ly
Nu
r
h
id
a
y
ati
✓
✓
✓
✓
✓
✓
✓
C
:
C
o
n
c
e
p
t
u
a
l
i
z
a
t
i
o
n
M
:
M
e
t
h
o
d
o
l
o
g
y
So
:
So
f
t
w
a
r
e
Va
:
Va
l
i
d
a
t
i
o
n
Fo
:
Fo
r
mal
a
n
a
l
y
s
i
s
I
:
I
n
v
e
s
t
i
g
a
t
i
o
n
R
:
R
e
so
u
r
c
e
s
D
:
D
a
t
a
C
u
r
a
t
i
o
n
O
:
W
r
i
t
i
n
g
-
O
r
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g
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n
a
l
D
r
a
f
t
E
:
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r
i
t
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g
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R
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v
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e
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&
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d
i
t
i
n
g
Vi
:
Vi
su
a
l
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z
a
t
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Su
:
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p
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r
v
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s
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P
:
P
r
o
j
e
c
t
a
d
mi
n
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st
r
a
t
i
o
n
Fu
:
Fu
n
d
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n
g
a
c
q
u
i
si
t
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o
n
CO
NF
L
I
C
T
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F
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N
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R
E
S
T
ST
A
T
E
M
E
NT
Au
th
o
r
s
s
tate
n
o
co
n
f
lict o
f
in
t
er
est.
DATA
AV
AI
L
AB
I
L
I
T
Y
T
h
e
d
ata
th
at
s
u
p
p
o
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t
th
e
f
in
d
in
g
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o
f
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is
s
tu
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ar
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av
ailab
l
e
f
r
o
m
th
e
co
r
r
esp
o
n
d
in
g
au
t
h
o
r
,
[
HS
]
,
u
p
o
n
r
ea
s
o
n
ab
le
r
eq
u
est.
RE
F
E
R
E
NC
E
S
[
1
]
Z.
Zh
e
n
g
,
X
.
L
i
n
,
L.
C
h
e
n
,
C
.
Y
a
n
,
a
n
d
T
.
S
u
n
,
“
Ef
f
e
c
t
s
o
f
u
r
b
a
n
i
z
a
t
i
o
n
a
n
d
t
o
p
o
g
r
a
p
h
y
o
n
t
h
e
r
ma
l
c
o
mf
o
r
t
d
u
r
i
n
g
a
h
e
a
t
w
a
v
e
e
v
e
n
t
:
A
c
a
se
st
u
d
y
o
f
F
u
z
h
o
u
,
C
h
i
n
a
,
”
S
u
st
a
i
n
a
b
l
e
C
i
t
i
e
s
a
n
d
S
o
c
i
e
t
y
,
v
o
l
.
1
0
2
,
p
.
1
0
5
2
3
3
,
M
a
r
.
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
scs.
2
0
2
4
.
1
0
5
2
3
3
.
[
2
]
Y
.
Z
h
a
o
,
J.
Y
a
n
g
,
Z.
F
a
n
g
,
X
.
Z
h
a
n
g
,
T
.
G
u
o
,
a
n
d
Y
.
Li
,
“
P
a
ss
i
v
e
d
e
s
i
g
n
st
r
a
t
e
g
i
e
s
t
o
i
m
p
r
o
v
e
s
t
u
d
e
n
t
t
h
e
r
mal
c
o
mf
o
r
t
:
a
f
i
e
l
d
st
u
d
y
i
n
s
e
mi
-
o
u
t
d
o
o
r
sp
a
c
e
s
o
f
a
c
a
d
e
mi
c
b
u
i
l
d
i
n
g
s
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n
h
o
t
-
h
u
mi
d
a
r
e
a
s,”
U
rb
a
n
C
l
i
m
a
t
e
,
v
o
l
.
5
3
,
p
.
1
0
1
8
0
7
,
J
a
n
.
2
0
2
4
,
d
o
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:
1
0
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1
0
1
6
/
j
.
u
c
l
i
m
.
2
0
2
4
.
1
0
1
8
0
7
.
[
3
]
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