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ad
Hald
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ail:
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b
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m
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ticu
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w
ell
-
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a
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th
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w
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ld
[
1
]
.
T
h
e
ar
ea
in
I
n
d
o
n
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lo
ca
t
ed
at
th
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eq
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m
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m
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p
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p
s
[
2
]
.
A
g
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is
an
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x
tr
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m
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l
y
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an
d
d
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p
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u
s
tr
y
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i
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ce
it
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in
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x
tr
icab
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li
n
k
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to
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d
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t
h
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f
o
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d
in
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h
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co
m
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w
it
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t
h
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f
ac
t
th
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v
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tal
co
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ar
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[
3
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
2089
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4
8
6
4
I
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t J
R
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f
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ab
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&
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m
b
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Sy
s
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Vo
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13
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No
.
3
,
No
v
e
m
b
er
20
24
:
595
-
603
596
T
h
e
w
o
r
ld
o
f
ag
r
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lt
u
r
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is
in
d
ir
e
n
ee
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o
f
tech
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o
lo
g
y
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esp
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iall
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th
at
u
tili
ze
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t
h
e
in
ter
n
et
o
f
t
hi
n
g
s
(
I
o
T
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[
4
]
,
[
5
]
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I
o
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c
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tain
s
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s
i
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,
a
n
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s
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et
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o
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il
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m
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u
to
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o
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ased
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s
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b
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[
6
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.
No
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ar
m
in
g
ca
n
also
b
e
co
m
b
i
n
ed
w
it
h
ar
ti
f
icia
l
i
n
te
llig
e
n
ce
(
A
I
)
tech
n
o
lo
g
ie
s
t
o
in
cr
ea
s
e
m
a
x
i
m
u
m
r
es
u
lt
s
[
7
]
.
Desp
ite
th
eir
n
u
m
er
o
u
s
ad
v
a
n
tag
e
s
,
I
o
T
t
o
o
ls
[
8
]
r
em
ai
n
d
if
f
ic
u
lt to
i
m
p
le
m
en
t f
o
r
r
u
r
al
f
ar
m
er
s
.
T
h
e
r
esu
lts
o
f
I
o
T
[
9
]
s
en
s
in
g
d
ev
ices
ar
e
r
a
w
d
ata
th
at
ca
n
b
e
p
r
o
ce
s
s
ed
to
b
ec
o
m
e
a
r
ec
o
m
m
e
n
d
atio
n
o
r
ev
en
f
o
r
ec
ast
d
ata
f
o
r
th
e
f
u
t
u
r
e
o
f
s
o
il
co
n
ten
t
.
M
ac
h
in
e
lear
n
i
n
g
(
M
L
)
,
w
h
ic
h
is
o
n
e
o
f
th
e
d
er
iv
ati
v
es
o
f
AI
,
ca
n
h
el
p
an
d
ev
en
i
m
p
r
o
v
e
t
h
e
q
u
ali
t
y
o
f
t
h
e
h
ar
v
est
[
1
0
]
.
ML
h
a
s
m
a
n
y
t
h
i
n
g
s
t
h
at
d
ec
r
ea
s
e
h
u
m
a
n
in
v
o
l
v
e
m
e
n
t
o
r
in
cr
ea
s
e
o
u
tco
m
e
s
[
1
0
]
.
Of
ten
u
s
ed
m
e
th
o
d
s
ar
e
r
an
d
o
m
f
o
r
est
(
R
F)
,
l
in
ea
r
r
eg
r
ess
io
n
,
o
r
ex
tr
em
e
g
r
ad
ie
n
t
b
o
o
s
t
(
XGB
o
o
s
t
)
.
I
n
a
d
d
itio
n
,
th
er
e
is
also
th
e
u
s
e
o
f
u
s
in
g
d
ee
p
lear
n
in
g
(
DL
)
.
T
h
e
f
u
n
d
a
m
e
n
tal
d
i
f
f
er
en
ce
is
th
a
t
M
L
r
eq
u
ir
es
d
ata
to
p
er
f
o
r
m
clas
s
i
f
icatio
n
,
w
h
i
l
e
DL
d
o
es
n
o
t
n
ee
d
it b
ec
au
s
e
it
w
il
l d
o
th
e
clu
s
ter
in
g
i
ts
el
f
.
A
b
io
y
e
et
a
l.
[
1
1
]
r
esear
ch
in
g
f
r
e
s
h
w
a
ter
th
at
a
f
f
ec
ts
t
h
e
s
u
p
p
l
y
o
f
n
u
tr
ie
n
ts
a
n
d
ir
r
i
g
at
io
n
w
h
er
e
p
lan
t
g
r
o
w
t
h
i
s
n
ee
d
ed
b
ec
au
s
e
it is
u
s
ed
w
h
e
n
th
er
e
i
s
a
lac
k
o
f
r
ain
f
all.
A
cc
o
r
d
in
g
to
s
t
u
d
ies,
p
lan
t a
cti
v
it
ies
r
eq
u
ir
e
r
o
u
g
h
l
y
7
0
%
o
f
av
ai
la
b
le
w
ater
;
th
u
s
,
r
esp
o
n
s
ib
le
wate
r
co
n
s
u
m
p
tio
n
m
a
n
a
g
e
m
en
t
is
n
ec
ess
ar
y
.
T
h
is
S
tu
d
y
i
n
v
e
s
ti
g
ates
i
n
t
e
g
r
atin
g
d
if
f
er
en
t
m
ac
h
i
n
e
lear
n
i
n
g
m
o
d
el
s
(
ML
)
th
at
ca
n
p
r
o
v
id
e
o
p
tim
al
ir
r
ig
atio
n
m
an
a
g
e
m
e
n
t
d
ec
is
io
n
s
.
D
u
b
o
i
s
et
a
l.
[
7
]
m
a
k
e
s
a
g
r
ic
u
ltu
r
al
d
ec
is
io
n
s
b
ec
a
u
s
e
i
t
is
an
e
s
s
e
n
tial
co
m
p
o
n
en
t
i
n
s
ee
in
g
t
h
e
r
es
u
lts
in
t
h
e
f
u
tu
r
e.
I
n
th
e
s
cien
ce
a
n
d
co
n
te
x
t
o
f
in
te
lli
g
en
t
a
g
r
ic
u
lt
u
r
e,
f
ar
m
er
s
n
ee
d
d
ata
f
r
o
m
s
en
s
in
g
d
ev
ice
s
e
m
b
ed
d
ed
in
cr
o
p
s
,
lev
er
ag
i
n
g
a
g
r
o
n
o
m
ic
m
o
d
el
s
to
h
elp
.
T
h
e
r
esear
ch
f
o
c
u
s
e
s
on
d
em
o
n
s
tr
ati
n
g
t
h
e
r
elatio
n
s
h
i
p
b
et
w
ee
n
ML
in
s
o
lv
i
n
g
p
r
o
b
lem
s
as
e
x
p
lai
n
ed
p
r
ev
io
u
s
l
y
i
s
b
ec
au
s
e
t
h
is
m
et
h
o
d
ca
n
m
a
x
i
m
ize
p
r
ed
ictio
n
s
ac
cu
r
atel
y
.
R
ah
m
an
et
a
l
.
[
1
2
]
in
h
is
r
e
s
e
a
r
ch
o
n
s
ta
t
is
t
ic
s
,
ag
r
i
cu
l
tu
r
e
m
ak
es
a
s
ig
n
if
i
c
an
t
c
o
n
tr
i
b
u
ti
o
n
to
m
u
s
h
r
o
o
m
f
a
r
m
in
g
in
th
e
m
a
r
k
e
t
.
T
h
e
r
ef
o
r
e
,
th
e
p
o
p
u
l
a
r
ity
o
f
m
u
s
h
r
o
o
m
cu
l
t
iv
at
i
o
n
i
s
n
e
e
d
e
d
.
F
a
r
m
e
r
s
,
e
s
p
e
c
i
al
ly
in
r
em
o
t
e
a
r
e
a
s
,
ty
p
ic
a
l
ly
s
t
i
ll
em
p
l
o
y
t
r
a
d
it
i
o
n
a
l
m
e
t
h
o
d
s
t
o
m
o
n
i
t
o
r
c
r
u
c
i
al
f
a
c
t
o
r
s
in
f
u
n
g
al
g
r
o
w
th
,
s
u
c
h
as
t
em
p
e
r
at
u
r
e
,
h
u
m
i
d
ity
,
a
n
d
p
H
c
o
n
d
i
t
i
o
n
s
.
A
s
a
r
e
s
u
l
t
,
t
h
e
f
o
cu
s
o
f
th
is
r
e
s
e
a
r
ch
is
o
n
u
s
i
n
g
ML
an
d
I
o
T
a
r
c
h
it
e
c
tu
r
e
t
o
c
o
n
s
t
r
u
c
t
s
m
a
r
t
m
u
s
h
r
o
o
m
f
a
r
m
in
g
w
ith
ex
ce
p
t
i
o
n
al
r
esu
l
ts
.
A
s
tu
d
y
c
o
n
d
u
c
t
e
d
t
r
i
al
s
o
n
ML
t
e
c
h
n
o
l
o
g
y
h
as
b
e
en
a
d
o
p
t
e
d
to
c
l
a
s
s
if
y
f
u
n
g
i
u
s
in
g
ML
m
o
d
e
l
s
s
u
ch
as
lin
e
a
r
r
eg
r
es
s
i
o
n
(
L
R
)
,
d
e
c
is
i
o
n
t
r
e
e
(
D
T
)
,
k
-
n
e
a
r
es
t
n
e
ig
h
b
o
u
r
(
KN
N
)
,
n
aïv
e
b
ay
es
(
N
B
)
,
s
u
p
p
o
r
t
v
e
c
t
o
r
m
a
ch
in
e
(
SV
M
)
,
an
d
R
F
.
T
h
e
h
ig
h
es
t
a
c
c
u
r
ac
y
g
a
in
e
d
w
ith
th
e
en
s
em
b
l
e
m
o
d
el
is
1
0
0
%
.
W
i
d
i
an
t
o
e
t
a
l
.
[
5
]
i
s
a
p
r
ev
i
o
u
s
s
tu
d
y
th
a
t
is
th
e
b
as
is
o
f
t
h
is
s
tu
d
y
.
I
n
a
p
r
e
v
i
o
u
s
s
tu
d
y
,
th
e
a
u
th
o
r
c
o
n
d
u
c
te
d
a
s
u
r
v
ey
to
c
o
l
l
e
c
t
d
a
t
a
in
m
o
u
n
ta
in
o
u
s
a
r
e
a
s
.
T
h
e
r
e
s
e
a
r
ch
r
e
s
u
l
ts
f
o
cu
s
o
n
g
en
e
r
a
t
in
g
d
a
t
a
u
ti
l
i
zin
g
I
o
T
t
o
o
l
s
.
N
ex
t
,
th
e
r
o
o
t
m
e
an
s
q
u
a
r
e
d
e
r
r
o
r
(
R
M
S
E
)
e
r
r
o
r
m
e
asu
r
em
en
t
w
a
s
c
a
r
r
i
e
d
o
u
t
b
y
c
o
m
p
a
r
in
g
th
e
r
esu
l
ts
f
r
o
m
I
o
T
w
i
th
th
e
a
c
tu
a
l
v
a
lu
e
,
b
u
t
n
o
t
y
e
t
u
t
i
li
z
in
g
M
L
m
o
d
e
ls
.
A
c
c
o
r
d
in
g
t
o
s
ev
e
r
a
l
s
t
u
d
i
es
,
f
ew
h
av
e
a
p
p
li
e
d
o
r
i
g
i
n
a
l
d
a
t
a
f
r
o
m
I
n
d
o
n
e
s
i
a'
s
u
n
i
q
u
e
r
e
g
i
o
n
s
,
es
p
e
c
ia
l
l
y
W
e
s
t
J
a
v
a
.
B
e
c
au
s
e
th
e
n
atu
r
e
o
f
t
h
e
d
a
ta
f
r
o
m
t
em
p
e
r
a
tu
r
e
,
p
H
,
a
n
d
h
u
m
i
d
ity
v
a
r
i
e
s
f
r
o
m
c
o
u
n
t
r
y
t
o
c
o
u
n
t
r
y
,
b
y
u
s
in
g
ML
,
th
e
au
th
o
r
c
an
f
o
r
e
c
a
s
t
s
o
m
e
o
f
th
es
e
f
e
a
tu
r
es
t
o
h
e
l
p
f
a
r
m
e
r
s
a
t
t
h
e
f
o
r
e
f
r
o
n
t
.
T
h
is
r
esear
ch
co
n
tr
ib
u
te
s
to
a
co
m
p
ar
ati
v
e
m
o
d
el
o
f
s
e
v
er
al
ML
m
eth
o
d
s
t
h
at
ca
n
b
e
as
s
es
s
ed
o
n
th
e
R
MSE
r
es
u
lts
a
n
d
ab
s
o
lu
te
er
r
o
r
,
to
s
ea
r
ch
f
o
r
th
e
b
est r
esu
lt
s
in
s
o
il c
o
n
d
itio
n
f
o
r
ec
asti
n
g
f
o
r
f
ar
m
er
s
.
I
n
th
i
s
s
tu
d
y
,
s
ev
er
al
al
g
o
r
ith
m
s
w
i
ll
b
e
u
s
ed
to
p
er
f
o
r
m
co
m
p
ar
is
o
n
s
,
s
u
ch
a
s
DT
[
1
3
]
,
[
1
4
]
,
RF
[
1
5
]
,
[
1
6
]
,
LR
[
1
7
]
,
[
1
8
]
,
an
d
XGB
o
o
s
t
[
1
9
]
,
[
2
0
]
.
B
y
u
s
i
n
g
t
h
is
al
g
o
r
ith
m
,
it
c
an
b
e
s
ee
n
w
h
ich
p
er
f
o
r
m
a
n
c
e
p
r
o
d
u
ce
s
th
e
b
est
p
r
ed
ictio
n
s
.
I
t
is
h
o
p
ed
th
at
r
u
r
al
f
ar
m
er
s
ca
n
u
s
e
it
w
it
h
d
ata
tak
en
f
r
o
m
I
o
T
d
ev
ices
o
n
a
s
ec
o
n
d
ar
y
b
asis
(
d
ata
r
etr
iev
al
h
as
b
ee
n
ca
r
r
ied
o
u
t
f
o
r
s
ev
er
al
m
o
n
t
h
s
)
.
Af
ter
u
n
d
er
s
ta
n
d
in
g
t
h
e
b
ac
k
g
r
o
u
n
d
o
f
w
h
y
M
L
i
s
n
ee
d
ed
in
f
o
r
ec
asti
n
g
,
th
e
n
e
x
t
ch
ap
ter
w
i
ll
d
is
cu
s
s
th
eo
r
y
(
c
h
ap
ter
2
)
,
s
y
s
te
m
d
esig
n
(
ch
ap
ter
3
)
,
r
esu
lts
(
ch
ap
ter
4
)
,
an
d
co
n
clu
s
io
n
s
(
ch
ap
ter
5
)
.
I
t is h
o
p
ed
th
at
t
h
is
r
esear
ch
ca
n
b
e
u
s
ed
f
o
r
f
u
r
t
h
e
r
r
esear
ch
o
r
o
th
er
in
d
u
s
tr
ies
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
2
.
1
.
I
nte
rnet
o
f
t
hin
g
s
T
h
is
tech
n
o
lo
g
y
is
a
s
y
s
te
m
f
o
r
co
n
n
ec
tin
g
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w
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r
k
[
2
1
]
.
I
n
th
i
s
s
t
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y
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I
o
T
i
s
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I
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d
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W
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av
a
R
eg
io
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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t J
R
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o
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f
i
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&
E
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b
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d
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Sy
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I
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N:
2089
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4864
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tech
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ca
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s
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f
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s
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w
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d
d
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li
v
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k
ap
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s
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a
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d
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elp
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tech
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ies s
u
c
h
as I
o
T
,
b
ig
d
ata
(
B
D)
,
A
I
,
ML
[
2
2
]
,
an
d
DL
[
2
3
]
.
A
ll
o
f
t
h
e
p
r
ev
io
u
s
s
i
g
n
if
ica
n
tl
y
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m
p
ac
t
s
m
ar
t
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ar
m
i
n
g
as
it
ca
n
d
eliv
er
th
e
en
tire
s
u
p
p
ly
c
h
ain
,
esp
ec
iall
y
in
p
r
o
d
u
ci
n
g
ess
e
n
tial
cr
o
p
s
s
u
c
h
as
i
n
(
f
o
r
I
n
d
o
n
esia
n
s
)
.
All
co
m
p
o
n
e
n
t
s
ar
e
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n
s
id
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ed
in
in
cr
ea
s
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n
g
t
h
e
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ar
iet
y
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n
d
a
m
o
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o
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e
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T
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th
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ata
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tly
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s
'
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p
er
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o
r
m
an
ce
o
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t
h
e
M
L
al
g
o
r
ith
m
[
2
4
]
.
T
h
e
s
y
s
te
m
ca
n
s
ee
th
e
f
lo
w
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et
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f
t
w
ar
e
an
d
h
ar
d
w
ar
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co
m
p
o
n
en
t
s
[
25]
.
T
h
is
tech
n
o
lo
g
y
h
as
also
b
ec
o
m
e
o
n
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ies
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n
M
L
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ed
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is
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h
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2
.
3
.
M
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A
I
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as
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o
f
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ap
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ter
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it
h
litt
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u
m
an
in
v
o
l
v
e
m
en
t
[
2
6
]
.
T
h
er
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o
r
e,
th
is
r
elate
s
to
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ar
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s
o
th
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r
o
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lem
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au
s
e
in
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ig
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ce
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eq
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ir
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ea
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n
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e
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lan
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g
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m
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o
n
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tio
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to
r
ef
er
to
d
if
f
er
e
n
t
m
eth
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d
s
an
d
to
o
ls
[
2
7
]
.
Ho
w
e
v
er
,
th
e
s
ch
e
m
e
h
as
f
ac
ed
s
e
v
er
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o
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s
tacle
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d
u
e
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h
e
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n
iq
u
e
n
a
tu
r
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o
f
h
u
m
an
s
,
w
h
o
al
w
a
y
s
s
tr
u
g
g
le
to
ex
p
lai
n
all
k
n
o
w
led
g
e
in
a
co
m
p
le
x
m
an
n
er
[
2
8
]
.
ML
,
o
n
t
h
e
o
th
er
h
a
n
d
,
ca
n
o
v
er
co
m
e
th
e
s
e
o
b
s
tacle
s
;
M
L
ca
n
i
m
p
r
o
v
e
p
r
o
g
r
a
m
p
er
f
o
r
m
a
n
ce
b
y
tak
i
n
g
p
r
io
r
e
x
p
er
ien
ce
an
d
p
er
f
o
r
m
an
ce
m
ea
s
u
r
es
[
2
9
]
.
T
h
er
ef
o
r
e,
ML
ca
n
au
to
m
ate
t
h
e
task
o
f
b
u
ild
i
n
g
an
al
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tical
m
o
d
el
s
th
at
ar
e
co
g
n
i
tiv
e
in
n
at
u
r
e
in
p
er
f
o
r
m
i
n
g
la
n
g
u
a
g
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o
r
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b
j
ec
t
d
etec
ti
o
n
b
ec
au
s
e
M
L
ca
n
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m
p
le
m
en
t
p
r
o
g
r
a
m
s
th
at
ca
n
lear
n
f
r
o
m
tr
ain
in
g
d
ata.
ML
ca
n
b
e
ap
p
lied
w
e
ll,
esp
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iall
y
w
h
e
n
th
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tas
k
is
r
elate
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to
d
ata
w
it
h
m
a
n
y
f
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tu
r
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r
eg
r
es
s
i
o
n
,
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i
f
icatio
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,
an
d
clu
s
ter
i
n
g
.
B
y
lear
n
in
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f
r
o
m
p
r
ev
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s
ex
p
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ce
s
,
ML
ca
n
h
elp
p
r
o
d
u
ce
r
eliab
le
an
d
r
e
p
ea
tab
le
d
ec
is
io
n
s
[
3
0
]
.
T
h
is
s
tu
d
y
w
ill
u
s
e
s
e
v
er
al
r
esear
ch
alg
o
r
it
h
m
s
u
s
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n
g
ML
,
s
u
c
h
as
R
F,
L
R
,
DT
,
an
d
XGB
o
o
s
t.
2.
3
.
1
.
L
inea
r
re
g
re
s
s
io
n
T
h
er
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ar
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m
an
y
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r
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s
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els.
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h
is
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al
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s
is
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s
u
s
e
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u
l
in
est
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m
at
in
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t
h
e
v
ar
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le
's
v
a
lu
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t
h
e
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ep
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ex
a
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'y
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it
h
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s
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f
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t
o
n
t
h
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n
d
ep
en
d
en
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v
ar
iab
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'
x
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[
3
1
]
.
Ho
w
e
v
er
,
th
i
s
s
tu
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y
o
n
l
y
f
o
c
u
s
e
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li
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r
eg
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io
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.
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h
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a
lg
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r
ith
m
is
a
m
o
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el
w
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th
t
h
e
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r
r
eg
r
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s
s
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a
s
th
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(
1
)
:
=
+
(
1
)
w
h
er
e
=
th
e
d
ep
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d
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t v
ar
iab
le
;
=
th
e
ex
p
la
n
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r
y
v
ar
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le
;
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=
t
h
e
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ter
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;
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h
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th
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T
h
e
(
1
)
is
a
s
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m
p
le
f
o
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m
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la
f
o
r
p
er
f
o
r
m
i
n
g
LR
.
T
h
i
s
al
g
o
r
ith
m
ca
n
d
is
t
in
g
u
is
h
t
h
e
e
f
f
ec
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b
et
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n
th
ese
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ar
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les
.
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w
e
v
er
,
t
h
is
alg
o
r
ith
m
is
o
n
l
y
u
s
ed
as
a
s
i
m
p
le
p
r
ed
ictiv
e
m
ea
s
u
r
e
m
e
n
t
,
s
o
th
e
r
e
s
u
l
ts
ar
e
u
n
l
ik
el
y
to
b
e
g
o
o
d
f
o
r
d
iv
er
s
e
d
ata
[
3
2
]
.
2.
3
.
2
.
Ra
nd
o
m
f
o
re
s
t
RF
[
1
5
]
alg
o
r
it
h
m
h
a
s
a
tr
ee
f
o
r
m
ak
i
n
g
d
ec
is
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n
s
th
at
ca
n
b
e
in
ter
p
r
eted
w
ith
a
p
ar
a
m
et
r
ic
m
o
d
el.
Do
n
e
to
in
teg
r
ate
DT
an
al
y
s
i
s
,
p
r
e
d
ictio
n
m
o
d
els
lik
e
th
is
c
an
b
e
s
aid
to
b
e
m
o
r
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co
m
p
r
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h
en
s
i
v
e
to
co
n
clu
d
e.
RF
r
eg
r
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n
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s
a
n
o
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-
p
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m
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tr
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r
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r
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o
r
ith
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d
er
iv
ed
f
r
o
m
a
tr
ee
.
2.
3
.
3
.
Dec
is
io
n
t
re
e
T
h
is
alg
o
r
ith
m
i
s
o
n
e
o
f
t
h
e
ML
t
h
at
i
s
o
f
te
n
u
s
ed
b
ec
au
s
e
it
is
a
p
o
p
u
lar
clas
s
i
f
ier
.
B
ec
au
s
e
t
h
i
s
alg
o
r
ith
m
m
o
d
el
i
s
ea
s
y
to
ex
p
lain
,
o
n
e
o
f
t
h
e
m
ca
n
p
er
f
o
r
m
v
er
y
s
ati
s
f
ac
to
r
il
y
.
DT
is
w
i
d
ely
u
s
ed
b
ec
au
s
e
o
f
th
e
in
cr
ea
s
in
g
n
ee
d
to
u
s
e
M
L
m
o
d
els
.
T
h
is
m
o
d
el
also
h
a
s
m
an
y
d
er
iv
ati
v
es,
s
o
m
a
n
y
s
a
y
t
h
at
DT
is
o
n
e
o
f
th
e
b
ases
o
f
s
ev
er
al
m
o
d
els
[
3
3
]
.
2.
3
.
4
.
XG
B
o
o
s
t
T
h
is
alg
o
r
ith
m
,
u
s
u
all
y
ca
lled
XGB
o
o
s
t
is
a
b
o
o
s
t
in
th
e
d
e
cisi
o
n
m
et
h
o
d
[
3
4
]
.
T
h
is
alg
o
r
ith
m
is
a
n
i
m
p
le
m
en
ta
tio
n
o
f
t
h
e
g
r
ad
ien
t
ad
d
er
en
g
in
e
(
GB
M
)
.
T
h
is
alg
o
r
ith
m
ca
n
b
e
u
s
ed
f
o
r
s
e
v
er
al
class
i
f
icat
io
n
an
d
r
eg
r
ess
io
n
p
r
o
b
le
m
s
.
Da
ta
r
esear
ch
er
s
v
er
y
m
u
c
h
n
e
ed
th
is
alg
o
r
it
h
m
e
be
ca
u
s
e
i
t
h
as
a
v
er
y
h
ig
h
co
m
p
u
tatio
n
al
s
p
ee
d
w
h
e
n
v
ie
w
ed
i
n
co
r
e
co
m
p
u
tin
g
[
3
5
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2089
-
4
8
6
4
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t
,
Vo
l.
13
,
No
.
3
,
No
v
e
m
b
er
20
24
:
595
-
603
598
2.
3
.
5
.
M
a
t
rix
co
rr
ela
t
io
n
T
h
er
e
a
r
e
n
u
m
er
o
u
s
m
atr
ice
s
to
o
b
s
er
v
e;
h
o
w
e
v
er
,
in
th
is
s
t
u
d
y
,
th
e
au
t
h
o
r
f
o
cu
s
e
s
o
n
th
e
co
r
r
elatio
n
m
atr
ix
,
w
h
er
e
a
m
atr
ix
h
a
s
a
co
r
r
elatio
n
co
ef
f
ic
ien
t
w
it
h
v
al
u
es
lo
ca
ted
in
th
e
in
ter
v
a
l
[
-
1
,
1
]
.
A
co
r
r
elatio
n
co
ef
f
icie
n
t
is
p
ar
t
o
f
a
v
al
u
e
to
s
ee
h
o
w
clo
s
el
y
th
e
r
elatio
n
s
h
ip
b
et
w
ee
n
v
ar
i
ab
les
is
w
it
h
o
th
er
v
ar
iab
les.
T
h
e
s
et
o
f
co
e
f
f
icie
n
ts
is
p
r
ese
n
ted
i
n
a
co
r
r
elati
o
n
m
a
tr
ix
[
3
6
]
.
T
h
e
co
r
r
elatio
n
f
o
r
m
u
la
its
e
lf
is
f
o
u
n
d
in
(
2
)
[
3
7
]
:
=
∑
(
−
_
)
(
−
_
)
√
∑
(
−
_
)
2
√
∑
(
−
_
)
2
(
2
)
w
h
ic
h
=c
o
r
r
elatio
n
co
ef
f
icien
t
;
=d
ata
x
;
_
=
d
ata
av
er
ag
e
;
=d
ata
;
_
=d
ata
av
er
ag
e
.
T
h
e
(
2
)
f
o
r
ea
ch
co
r
r
elatio
n
b
et
w
ee
n
v
ar
iab
le
s
w
ill
b
e
m
ap
p
ed
in
a
h
ea
t
m
ap
to
s
h
o
w
th
e
r
elatio
n
s
h
ip
's
s
ize.
C
o
r
r
elatio
n
an
al
y
s
is
is
u
s
u
all
y
u
s
ed
in
s
ta
tis
tical
m
ea
s
u
r
es
t
h
at
ca
n
b
e
u
s
ed
in
d
ep
th
to
s
ee
d
if
f
er
e
n
t
s
t
u
d
y
s
it
u
atio
n
s
f
r
o
m
an
ef
f
icie
n
t
id
en
tific
atio
n
o
f
r
elatio
n
s
h
ip
s
b
et
w
ee
n
o
th
er
att
r
ib
u
tes
o
f
a
d
ataset
o
b
tain
ed
f
r
o
m
I
o
T
to
o
ls
(
s
ee
Fig
u
r
e
1)
[
3
8
]
.
Data
h
a
s
a
p
o
s
it
iv
e
o
r
s
tr
o
n
g
p
o
s
itiv
e
co
r
r
elatio
n
i
f
it
co
n
ti
n
u
o
u
s
l
y
i
n
cr
ea
s
es
in
t
h
e
p
o
s
iti
v
e
d
ir
ec
tio
n
an
d
v
ice
v
er
s
a
f
o
r
n
eg
ati
v
e
an
d
s
tr
o
n
g
l
y
n
eg
a
tiv
e
co
r
r
elatio
n
s
.
O
n
t
h
e
co
n
tr
ar
y
,
if
t
h
e
d
ata
is
al
w
a
y
s
r
an
d
o
m
,
it
w
ill
b
e
s
aid
to
b
e
u
n
co
r
r
elate
d
.
Ho
w
e
v
er
,
if
th
e
co
r
r
elatio
n
r
esu
lt
s
f
o
r
m
a
h
ill,
it
ca
n
b
e
s
aid
to
h
av
e
a
n
o
n
-
lin
ea
r
co
r
r
elatio
n
.
Fig
u
r
e
1
.
T
y
p
e
o
f
co
r
r
elatio
n
[
3
8
]
2.
3
.
6
.
P
er
f
o
rm
a
nce
T
h
e
r
eg
r
ess
io
n
r
esu
lts
u
s
u
al
l
y
u
s
ed
s
ev
er
al
ap
p
r
o
ac
h
es,
an
d
th
is
s
tu
d
y
's
au
t
h
o
r
s
h
a
v
e
s
ev
er
al
ap
p
r
o
ac
h
es.
Un
ce
r
tain
t
y
i
s
u
s
ed
b
y
t
h
e
m
et
h
o
d
o
r
o
b
s
er
v
atio
n
is
u
s
ed
to
s
ee
t
h
e
r
esu
lts
o
f
th
e
co
m
p
ar
is
o
n
b
et
w
ee
n
o
b
s
er
v
er
s
an
d
t
h
e
m
o
d
el,
s
o
th
e
R
MSE
ap
p
r
o
ac
h
is
ap
p
lied
[
3
9
]
an
d
ab
s
o
lu
te
er
r
o
r
u
s
i
n
g
(
3
)
an
d
(
4
):
√
1
∑
2
=
1
(
3
)
(
∆
)
=
|
−
|
(
4
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t
I
SS
N:
2089
-
4864
S
ma
r
t fa
r
min
g
b
a
s
ed
o
n
I
o
T t
o
p
r
ed
ict
co
n
d
itio
n
s
u
s
in
g
ma
ch
in
e
lea
r
n
in
g
(
Mo
ch
a
mma
d
Ha
ld
i W
id
ia
n
to
)
599
in
(
3
)
an
d
(
4
)
is
o
n
e
w
a
y
to
f
i
n
d
th
e
p
er
f
o
r
m
a
n
ce
o
f
t
h
e
r
eg
r
ess
io
n
w
h
er
e
n
i
s
th
e
d
ata,
an
d
i
is
th
e
a
m
o
u
n
t
o
f
d
ata
av
ailab
le.
Af
ter
s
t
u
d
y
i
n
g
th
e
t
h
eo
r
y
u
s
ed
in
t
h
i
s
r
es
ea
r
ch
,
th
e
n
e
x
t
c
h
ap
ter
w
i
ll
ex
p
lain
t
h
e
s
y
s
te
m
's
d
esig
n
to
b
e
f
o
r
m
ed
.
3.
SYST
E
M
DE
SI
G
N
I
n
t
h
i
s
s
e
c
ti
o
n
,
th
e
au
th
o
r
w
i
ll
d
i
s
c
u
s
s
s
ev
e
r
a
l
d
e
s
ig
n
s
u
s
e
d
in
c
o
n
d
u
c
tin
g
th
is
r
e
s
ea
r
ch
.
A
c
c
o
r
d
i
n
g
t
o
t
h
e
au
th
o
r
,
th
es
e
d
es
ig
n
s
a
r
e
es
s
en
t
i
a
l
in
ex
p
l
ai
n
in
g
t
o
r
e
a
d
e
r
s
h
o
w
th
i
s
s
tu
d
y
w
o
r
k
s
.
T
h
e
r
ef
o
r
e
,
th
e
au
th
o
r
w
il
l
e
x
p
l
ai
n
h
o
w
th
e
r
e
s
e
a
r
ch
w
o
r
k
s
th
r
o
u
g
h
th
e
r
esu
l
ts
:
i
)
d
a
t
a
s
h
a
p
e
,
i
i
)
d
a
t
a
c
o
r
r
e
la
t
i
o
n
m
a
t
r
i
x
,
a
n
d
i
ii
)
ML
d
es
ig
n
.
3
.
1
.
Da
t
a
s
ha
pe
Data
is
r
etr
ie
v
ed
u
s
i
n
g
I
o
T
d
ev
ices
.
T
h
e
a
u
t
h
o
r
ca
n
cr
ea
te
ML
ap
p
licatio
n
s
co
m
b
i
n
ed
w
it
h
I
o
T
to
m
ak
e
ac
c
u
r
ate
p
r
ed
ictio
n
s
in
p
r
ed
ictin
g
te
m
p
er
atu
r
e
a
n
d
s
o
il
m
o
is
t
u
r
e.
A
n
alo
g
o
u
s
r
es
u
lts
w
er
e
o
b
tain
ed
th
r
o
u
g
h
g
ar
d
en
te
m
p
er
at
u
r
e,
s
o
il
m
o
is
t
u
r
e,
lig
h
t
r
esis
ta
n
ce
,
an
d
air
h
u
m
id
it
y
.
A
n
e
x
a
m
p
le
o
f
th
e
d
ata
f
o
r
m
is
s
h
o
w
n
i
n
T
ab
le
1
[
5
]
:
i)
w
e
m
o
s
D1
R
2
(
E
SP
8
2
6
6
)
,
ii)
c
a
p
ac
itiv
e
s
o
il
m
o
i
s
tu
r
e
s
e
n
s
o
r
,
iii)
lig
h
t
d
ep
en
d
en
t
r
esis
to
r
(
L
DR
)
p
h
o
to
r
esis
to
r
s
en
s
o
r
,
iv
)
t
e
m
p
er
atu
r
e
an
d
h
u
m
id
it
y
s
en
s
o
r
(
DHT
2
2
)
,
v
)
m
o
d
em
Wi
-
Fi
r
o
u
ter
,
an
d
v
i)
p
o
w
er
s
u
p
p
l
y
u
n
it
5
V/1
0
A
(
P
SU)
.
T
a
b
le
1
s
h
o
w
s
th
e
r
esu
lt
s
o
b
tain
ed
b
y
u
ti
lizin
g
I
o
T
s
en
s
in
g
d
ev
ices.
T
h
e
d
ata
w
i
ll
b
e
co
r
r
elate
d
,
w
h
ic
h
w
ill
t
h
e
n
b
e
u
s
e
d
to
s
ee
th
e
p
r
e
d
ictio
n
p
er
f
o
r
m
an
ce
o
f
s
ev
er
al
ML
w
it
h
te
m
p
er
atu
r
e
an
d
s
o
il
m
o
i
s
tu
r
e
p
r
ed
ictio
n
s
.
3
.
2
.
M
a
t
rix
co
rr
ela
t
i
o
n
a
nd
m
a
ch
ine le
a
rning
de
s
ig
n
As
p
r
ev
io
u
s
l
y
e
x
p
lain
ed
,
t
h
i
s
m
atr
i
x
h
elp
s
s
ee
th
e
r
elati
o
n
s
h
ip
b
et
w
ee
n
s
e
v
er
al
f
ea
t
u
r
es
in
th
e
d
atash
ee
t.
Fo
r
its
u
s
e,
it
u
tili
ze
s
R
ap
id
m
i
n
er
(
s
t
u
d
en
t
v
er
s
io
n
)
.
T
h
e
d
esig
n
i
s
d
iv
id
ed
in
to
2
p
ar
ts
:
i
)
d
is
cu
s
s
in
g
co
r
r
elatio
n
m
atr
i
x
d
esi
g
n
an
d
ii
)
d
is
cu
s
s
i
n
g
M
L
d
esi
g
n
.
T
h
e
d
esig
n
i
s
s
h
o
w
n
i
n
Fi
g
u
r
e
2
.
I
n
Fi
g
u
r
e
2
(
a)
th
e
d
ata
u
s
es
s
ec
o
n
d
ar
y
d
ata,
w
h
i
ch
is
p
r
o
ce
s
s
ed
b
y
d
ata
n
o
r
m
a
lizatio
n
,
th
e
n
u
s
i
n
g
(
2
)
,
th
e
co
r
r
elatio
n
r
esu
lt
s
ar
e
d
is
p
la
y
ed
.
I
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o
b
u
s
t c
o
r
r
elatio
n
w
it
h
o
th
er
f
ea
tu
r
es
.
T
ab
le
3
.
R
MSE
p
er
f
o
r
m
a
n
ce
ML
(
a)
te
m
p
er
atu
r
e
(
a
m
o
u
n
t o
f
tr
ain
i
n
g
d
ata
%/ to
tal
test
in
g
d
ata
%
)
an
d
(
b
)
s
o
il m
o
i
s
tu
r
e
(
a
m
o
u
n
t o
f
tr
ain
i
n
g
d
ata
%
/ to
tal
test
i
n
g
d
ata
%)
(
b
)
P
a
r
a
me
t
e
r
9
0
%/
1
0
%
8
0
%/
2
0
%
7
0
%/
3
0
%
L
R
(
R
M
S
E)
1
9
.
2
1
0
1
9
.
4
5
6
1
9
.
6
5
4
DT
(
R
M
S
E)
1
8
.
3
7
4
1
8
.
5
8
4
1
9
.
3
8
3
RF
(
R
M
S
E)
1
7
.
2
0
9
1
7
.
3
4
5
1
7
.
9
4
0
X
G
B
o
o
st
(
R
M
S
E)
1
7
.
1
5
1
1
7
.
3
3
4
1
7
.
9
9
3
T
ab
le
4
.
A
b
s
o
lu
te
er
r
o
r
p
er
f
o
r
m
an
ce
p
er
f
o
r
m
an
ce
ML
(
a)
te
m
p
er
at
u
r
e
(
a
m
o
u
n
t o
f
tr
ain
i
n
g
d
ata
%/ to
tal
test
i
n
g
d
ata
%
)
an
d
(
b
)
s
o
il
m
o
is
tu
r
e
(
a
m
o
u
n
t o
f
tr
ain
i
n
g
d
ata
%/ to
tal
test
i
n
g
d
ata
%)
(
b
)
P
a
r
a
me
t
e
r
90
%
/
1
0
%
80
%
/
2
0
%
70
%
/
3
0
%
LR
(
a
b
so
l
u
t
e
e
r
r
o
r
)
16.
066
15.
674
15.
730
DT
(
a
b
so
l
u
t
e
e
r
r
o
r
)
11.
477
11.
617
11.
853
RF
(
a
b
so
l
u
t
e
e
r
r
o
r
)
11.
578
11.
713
12.
144
X
G
B
o
o
st
(
a
b
so
l
u
t
e
e
r
r
o
r
)
11.
269
11.
486
11.
774
5.
CO
NCLU
SI
O
N
T
h
is
w
o
r
k
f
o
c
u
s
e
s
o
n
u
tili
zi
n
g
s
o
m
e
M
L
i
n
s
m
ar
t
f
ar
m
i
n
g
,
an
d
th
e
r
es
u
lt
in
g
d
ata
i
n
t
h
e
f
o
r
m
o
f
te
m
p
er
atu
r
e,
s
o
il
m
o
is
t
u
r
e,
lig
h
t
in
te
n
s
it
y
r
esi
s
ta
n
ce
,
an
d
h
u
m
id
it
y
.
A
ll
f
ea
t
u
r
es
ar
e
g
en
er
ated
f
r
o
m
f
ar
m
I
o
T
d
ev
ices.
T
h
ese
f
ea
t
u
r
es
g
en
er
ated
an
ab
u
n
d
an
ce
o
f
d
ata,
wh
ich
w
as
th
e
n
p
r
ed
icted
u
s
in
g
A
I
,
s
p
ec
if
ica
ll
y
th
e
A
I
b
r
an
ch
k
n
o
w
n
a
s
ML
.
Se
v
er
al
ML
al
g
o
r
ith
m
s
h
e
lp
p
r
ed
ictio
n
,
s
u
c
h
as
lin
ea
r
r
eg
r
e
s
s
io
n
,
DT
,
RF
,
an
d
XGB
o
o
s
t.
W
h
at
is
test
ed
in
th
is
w
o
r
k
is
th
e
co
r
r
elatio
n
b
etw
ee
n
f
ea
t
u
r
es
i
n
d
eter
m
i
n
in
g
f
ea
t
u
r
e
r
elatio
n
s
h
ip
s
an
d
p
r
ed
ictio
n
test
s
in
t
h
e
f
o
r
m
o
f
R
MSE
a
n
d
ab
s
o
lu
t
e
er
r
o
r
.
T
h
e
r
esu
lts
s
h
o
w
t
h
at
XGB
o
o
s
t
is
v
er
y
g
o
o
d
at
m
ak
in
g
p
r
ed
ictio
n
s
o
n
t
h
i
s
wo
r
k
w
it
h
t
h
e
te
m
p
er
at
u
r
e
f
ea
t
u
r
e,
th
e
R
M
SE
is
6
.
6
5
6
,
an
d
th
e
ab
s
o
lu
te
er
r
o
r
is
3
.
4
9
8
.
T
h
er
e
is
a
u
n
iq
u
en
e
s
s
w
h
en
co
m
p
ar
i
n
g
R
MSE
,
an
d
ab
s
o
lu
te
er
r
o
r
in
RF
an
d
DT
,
w
h
er
e
th
e
RF
is
b
etter
w
h
e
n
test
i
n
g
R
MSE
an
d
th
e
DT
is
b
etter
w
h
en
tr
y
in
g
ab
s
o
l
u
te
er
r
o
r
.
I
n
th
e
s
e
co
n
d
test
,
w
h
e
n
th
e
p
r
ed
ictio
n
is
p
lace
d
o
n
th
e
s
o
i
l
m
o
i
s
tu
r
e
f
ea
tu
r
e,
th
e
XGB
o
o
s
t
alg
o
r
ith
m
is
s
til
l
b
etter
,
w
it
h
o
n
l
y
t
h
e
v
alu
e
o
f
R
MSE
an
d
ab
s
o
lu
te
er
r
o
r
b
ei
n
g
m
o
r
e
s
ig
n
i
f
ica
n
t
.
T
h
is
is
d
u
e
to
th
e
n
at
u
r
e
an
d
t
y
p
e
o
f
d
ata
o
n
v
ar
io
u
s
s
o
i
l
m
o
is
t
u
r
e
f
ea
tu
r
e
s
.
T
h
e
last
r
e
s
u
lt
also
s
h
o
w
s
th
a
t
li
n
ea
r
r
eg
r
ess
io
n
i
s
t
h
e
w
o
r
s
t
i
n
b
o
th
test
s
.
T
h
is
is
v
er
y
r
ea
s
o
n
ab
le
b
ec
au
s
e
LR
i
s
n
o
t
s
en
s
iti
v
e
to
d
ata
th
at
is
n
o
t h
i
g
h
l
y
co
r
r
elate
d
.
RE
F
E
R
E
NC
E
S
[
1
]
E.
A
y
r
e
s,
A
.
C
o
l
l
i
a
n
d
e
r
,
M
.
H
.
C
o
s
h
,
J.
A
.
R
o
b
e
r
t
i
,
S
.
S
i
mk
i
n
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a
n
d
M
.
A
.
G
e
n
a
z
z
i
o
,
“
V
a
l
i
d
a
t
i
o
n
o
f
S
M
A
P
so
i
l
mo
i
s
t
u
r
e
a
t
t
e
r
r
e
st
r
i
a
l
n
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t
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l
e
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o
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i
c
a
l
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b
se
r
v
a
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o
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w
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k
(
N
EO
N
)
si
t
e
s
sh
o
w
p
o
t
e
n
t
i
a
l
f
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r
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i
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mo
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t
r
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v
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l
i
n
f
o
r
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st
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d
a
r
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a
s
,
”
I
EEE
J
o
u
r
n
a
l
o
f
S
e
l
e
c
t
e
d
T
o
p
i
c
s
i
n
Ap
p
l
i
e
d
E
a
rt
h
O
b
ser
v
a
t
i
o
n
s
a
n
d
R
e
m
o
t
e
S
e
n
s
i
n
g
,
v
o
l
.
1
4
,
p
p
.
1
0
9
0
3
–
1
0
9
1
8
,
2
0
2
1
,
d
o
i
:
1
0
.
1
1
0
9
/
JS
T
A
R
S
.
2
0
2
1
.
3
1
2
1
2
0
6
.
[
2
]
F
.
V
i
n
c
e
n
t
e
t
a
l
.
,
“
L
-
b
a
n
d
m
i
c
r
o
w
a
v
e
sat
e
l
l
i
t
e
d
a
t
a
a
n
d
mo
d
e
l
si
m
u
l
a
t
i
o
n
s
o
v
e
r
t
h
e
d
r
y
c
h
a
c
o
t
o
e
st
i
m
a
t
e
s
o
i
l
mo
i
st
u
r
e
,
so
i
l
t
e
mp
e
r
a
t
u
r
e
,
v
e
g
e
t
a
t
i
o
n
,
a
n
d
so
i
l
sal
i
n
i
t
y
,
”
I
EEE
J
o
u
rn
a
l
o
f
S
e
l
e
c
t
e
d
T
o
p
i
c
s
i
n
A
p
p
l
i
e
d
E
a
r
t
h
O
b
serv
a
t
i
o
n
s
a
n
d
Re
m
o
t
e
S
e
n
si
n
g
,
v
o
l
.
1
5
,
p
p
.
6
5
9
8
–
6
6
1
4
,
2
0
2
2
,
d
o
i
:
1
0
.
1
1
0
9
/
JS
T
A
R
S
.
2
0
2
2
.
3
1
9
3
6
3
6
.
[
3
]
G
.
P
a
t
r
i
z
i
,
A
.
B
a
r
t
o
l
i
n
i
,
L
.
C
i
a
n
i
,
V
.
G
a
l
l
o
,
P
.
S
o
mm
e
l
l
a
,
a
n
d
M
.
C
a
r
r
a
t
u
,
“
A
v
i
r
t
u
a
l
so
i
l
mo
i
st
u
r
e
se
n
so
r
f
o
r
smar
t
f
a
r
mi
n
g
u
s
i
n
g
d
e
e
p
l
e
a
r
n
i
n
g
,
”
I
EE
E
T
r
a
n
s
a
c
t
i
o
n
s
o
n
I
n
st
r
u
m
e
n
t
a
t
i
o
n
a
n
d
Me
a
su
r
e
m
e
n
t
,
v
o
l
.
7
1
,
2
0
2
2
,
d
o
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:
1
0
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1
1
0
9
/
TI
M
.
2
0
2
2
.
3
1
9
6
4
4
6
.
[
4
]
T
.
M
.
B
a
n
d
a
r
a
,
W
.
M
u
d
i
y
a
n
se
l
a
g
e
,
a
n
d
M
.
R
a
z
a
,
“
S
mart
f
a
r
m
a
n
d
mo
n
i
t
o
r
i
n
g
sy
st
e
m
f
o
r
me
a
su
r
i
n
g
t
h
e
e
n
v
i
r
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n
me
n
t
a
l
c
o
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d
i
t
i
o
n
u
si
n
g
w
i
r
e
l
e
ss
s
e
n
so
r
n
e
t
w
o
r
k
-
I
o
T
t
e
c
h
n
o
l
o
g
y
i
n
f
a
r
mi
n
g
,
”
i
n
2
0
2
0
5
t
h
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
I
n
n
o
v
a
t
i
v
e
T
e
c
h
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o
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o
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e
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l
l
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t
S
y
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e
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s
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n
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I
n
d
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st
r
i
a
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A
p
p
l
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c
a
t
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s
(
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I
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I
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I
A)
,
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o
v
.
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0
,
p
p
.
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–
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.
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o
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A
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9
0
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2
0
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0
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3
7
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3
0
.
[
5
]
M
.
H
.
W
i
d
i
a
n
t
o
,
B
.
G
h
i
l
c
h
r
i
s
t
,
G
.
G
i
o
v
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n
,
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.
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.
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y
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sari
,
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n
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Y
.
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.
S
e
t
i
a
w
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n
,
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D
e
v
e
l
o
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me
n
t
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r
n
e
t
o
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n
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,
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i
n
2
0
2
2
4
t
h
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n
t
e
rn
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t
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o
n
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l
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o
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re
n
c
e
o
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y
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e
t
i
c
s
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n
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n
t
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l
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t
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m
(
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C
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RI
S
)
,
O
c
t
.
2
0
2
2
,
p
p
.
1
–
6
.
d
o
i
:
1
0
.
1
1
0
9
/
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C
O
R
I
S
5
6
0
8
0
.
2
0
2
2
.
1
0
0
3
1
4
7
0
.
(
a)
P
a
r
a
me
t
e
r
9
0
%/
1
0
%
8
0
%/
2
0
%
7
0
%/
3
0
%
L
R
(
R
M
S
E)
9
.
7
8
4
9
.
8
2
4
9
.
8
3
7
DT
(
R
M
S
E)
7
.
5
7
5
7
.
7
4
4
7
.
9
4
7
RF
(
R
M
S
E)
7
.
0
1
3
7
.
2
4
4
7
.
3
2
5
X
G
B
o
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Evaluation Warning : The document was created with Spire.PDF for Python.