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lan
n
in
g
,
k
n
o
wled
g
e
ac
q
u
is
itio
n
,
an
d
r
ap
id
a
n
d
e
f
f
ec
tiv
e
m
an
ag
em
en
t
o
f
v
ar
i
o
u
s
is
s
u
es
.
T
h
ese
ca
p
ab
ilit
ies
in
clu
d
e
o
u
tag
e
m
an
ag
e
m
en
t,
f
r
au
d
d
etec
tio
n
,
o
p
tim
izatio
n
o
f
p
o
wer
d
is
tr
ib
u
ti
o
n
,
a
n
d
h
a
n
d
lin
g
p
o
ten
tial
s
ec
u
r
ity
b
r
ea
ch
es,
am
o
n
g
o
t
h
er
s
.
T
h
e
liter
atu
r
e
s
u
r
r
o
u
n
d
in
g
en
er
g
y
c
o
n
s
u
m
p
tio
n
an
d
its
r
am
if
icatio
n
s
o
n
clim
ate
ch
an
g
e
is
ex
ten
s
iv
e,
h
ig
h
lig
h
ti
n
g
th
e
u
r
g
en
t
n
ee
d
f
o
r
co
m
p
r
eh
e
n
s
iv
e
in
ter
v
en
tio
n
s
[
6
]
.
R
ec
en
t
r
ep
o
r
ts
u
n
d
er
s
co
r
e
th
at
n
ea
r
ly
8
0
%
o
f
ca
r
b
o
n
e
m
is
s
io
n
s
ar
e
lin
k
ed
to
ex
ce
s
s
iv
e
en
er
g
y
co
n
s
u
m
p
tio
n
,
p
o
s
itio
n
in
g
it
as
a
p
r
im
a
r
y
d
r
iv
er
o
f
e
n
v
ir
o
n
m
en
tal
in
s
t
ab
ilit
y
[
7
]
-
[
1
1
]
.
All
o
f
th
is
is
in
ac
co
r
d
an
ce
with
th
e
Un
ited
Natio
n
s
'
g
o
al
o
f
ac
h
iev
in
g
th
e
Su
s
tain
ab
le
Dev
elo
p
m
en
t
Go
als
(
SDGs
)
ar
o
u
n
d
th
e
wo
r
ld
.
T
h
e
s
e
tar
g
ets s
tr
ess
h
o
w
im
p
o
r
tan
t it
is
to
cu
t e
m
is
s
io
n
s
b
y
2
0
3
0
an
d
m
ak
e
it e
asier
f
o
r
p
e
o
p
le
to
g
et
to
r
e
n
ewa
b
le
en
er
g
y
s
o
u
r
ce
s
.
T
h
e
liter
atu
r
e
also
u
n
d
er
s
co
r
e
s
th
e
p
r
o
f
o
u
n
d
in
f
lu
en
ce
o
f
w
ea
th
er
co
n
d
itio
n
s
o
n
r
esid
e
n
tial
s
ec
to
r
s
,
p
ar
ticu
lar
ly
in
ass
o
ciatio
n
wi
th
s
m
ar
t
h
o
u
s
eh
o
ld
ap
p
lian
ce
s
.
C
ar
b
o
n
em
is
s
io
n
s
f
r
o
m
d
e
v
ices
lik
e
lig
h
tin
g
,
h
ea
tin
g
,
co
o
lin
g
,
an
d
v
ar
i
o
u
s
p
lu
g
d
e
v
ices
co
n
tr
ib
u
te
s
u
b
s
ta
n
tially
to
n
atio
n
al
-
lev
el
em
is
s
io
n
s
[
1
2
]
-
[
1
5
]
.
T
h
is
h
ig
h
lig
h
ts
th
e
p
o
ten
tial
f
o
r
m
itig
atin
g
clim
ate
im
p
ac
t
b
y
s
tr
ateg
ically
r
ed
u
cin
g
th
e
c
o
n
s
u
m
p
tio
n
o
f
s
u
ch
d
ev
ices
[
1
6
]
-
[
2
0
]
.
T
h
e
Of
f
ice
f
o
r
Natio
n
al
Statis
tics
in
th
e
UK
ju
s
t
is
s
u
ed
a
s
tu
d
y
t
h
at
lo
o
k
ed
at
h
o
w
clim
ate
ch
an
g
e
h
as
af
f
ec
ted
p
eo
p
le'
s
h
o
m
es
an
d
liv
in
g
c
o
n
d
itio
n
s
.
T
h
e
s
tu
d
y
f
o
u
n
d
th
at
d
wellin
g
s
an
d
o
th
er
r
esid
en
tial
b
u
ild
in
g
s
ar
e
r
esp
o
n
s
ib
le
f
o
r
2
6
%
o
f
th
e
g
r
ee
n
h
o
u
s
e
g
as
em
is
s
io
n
s
in
th
e
U
K
[
2
1
]
.
T
h
e
r
ep
o
r
t
h
ig
h
lig
h
ts
th
at,
in
2
0
2
0
,
No
r
th
er
n
I
r
elan
d
ex
h
ib
ited
th
e
h
i
g
h
est
d
o
m
esti
c
em
is
s
io
n
s
p
er
ca
p
ita,
s
u
r
p
ass
in
g
ev
en
L
o
n
d
o
n
in
e
m
is
s
io
n
s
p
er
s
q
u
ar
e
k
ilo
m
ete
r
.
No
ta
b
ly
,
ap
p
r
o
x
im
ately
3
4
%
o
f
ad
u
lt
s
m
ad
e
n
o
e
x
p
licit
life
s
ty
le
ch
an
g
es
aim
ed
at
m
itig
atin
g
em
is
s
io
n
s
[
2
1
]
-
[
2
3
]
.
A
s
u
r
v
ey
co
n
d
u
cted
o
n
life
s
ty
le
an
d
en
e
r
g
y
co
n
s
u
m
p
tio
n
u
n
d
er
s
co
r
es
th
e
p
o
ten
tial
f
o
r
p
o
s
itiv
e
c
h
an
g
es
in
h
o
u
s
eh
o
ld
e
n
er
g
y
ef
f
icie
n
cy
[
2
4
]
.
T
h
e
s
tu
d
y
s
u
g
g
ests
th
at
alter
atio
n
s
in
life
s
ty
le
ch
o
ices
ca
n
co
n
tr
ib
u
te
s
ig
n
if
ican
tly
to
en
er
g
y
co
n
s
er
v
atio
n
in
r
esid
en
tial
s
ettin
g
s
.
A
s
m
all
s
o
cial
ex
p
er
im
en
t
in
v
o
lv
i
n
g
7
7
%
o
f
ad
u
lts
d
em
o
n
s
tr
ated
th
at
life
s
ty
le
m
o
d
if
icatio
n
s
n
o
t
o
n
ly
lead
to
r
e
d
u
ce
d
en
er
g
y
c
o
n
s
u
m
p
tio
n
b
u
t
also
p
lay
a
cr
u
cial
r
o
le
in
m
itig
atin
g
em
is
s
io
n
s
[
2
5
]
-
[
2
6
]
.
I
n
o
u
r
r
esear
ch
,
we
u
tili
ze
d
a
s
m
ar
t
h
o
u
s
e
d
ataset
to
in
v
esti
g
ate
h
o
w
co
n
tex
tu
al
f
ac
to
r
s
s
u
ch
as
wea
th
er
co
n
d
itio
n
s
an
d
a
p
p
lian
ce
u
s
ag
e
in
f
lu
en
ce
o
v
er
all
h
o
u
s
eh
o
ld
en
er
g
y
c
o
n
s
u
m
p
tio
n
.
T
h
e
g
o
al
o
f
t
h
is
s
tu
d
y
was
to
em
p
lo
y
s
ix
d
if
f
er
en
t
m
ac
h
in
e
lear
n
in
g
m
o
d
els
to
tr
y
to
p
r
ed
ict
h
o
w
m
u
ch
en
er
g
y
wo
u
ld
b
e
u
s
e
d
o
v
e
r
th
e
n
ex
t
two
d
ay
s
.
T
h
e
m
o
d
els
wer
e
a
s
u
p
p
o
r
t
v
ec
to
r
r
eg
r
ess
o
r
,
a
g
r
a
d
ien
t
b
o
o
s
tin
g
r
eg
r
ess
o
r
,
a
r
a
n
d
o
m
f
o
r
est
r
eg
r
ess
o
r
,
an
d
a
lin
ea
r
r
eg
r
ess
i
on.
Ad
d
itio
n
ally
,
we
ev
alu
ated
th
e
p
e
r
f
o
r
m
an
ce
o
f
th
ese
m
o
d
els
u
s
in
g
m
et
r
ics
s
u
ch
as
m
ea
n
s
q
u
ar
e
d
er
r
o
r
(
MSE
)
a
n
d
R
-
s
q
u
ar
ed
v
al
u
es.
2.
UT
I
L
I
Z
A
T
I
O
N
O
F
M
ACH
I
NE
L
E
ARN
I
NG
T
O
AS
SE
S
S E
N
E
RG
Y
CO
NSU
M
P
T
I
O
N
T
h
e
d
a
t
a
s
e
t
e
n
co
m
p
a
s
s
e
s
m
et
e
r
r
e
a
d
in
g
s
f
o
r
to
t
a
l
e
l
e
c
t
r
ici
t
y
co
n
s
u
m
p
t
io
n
,
a
s
we
l
l
a
s
e
l
e
c
t
r
i
c
i
ty
c
o
n
s
u
m
p
t
io
n
r
e
ad
i
n
g
s
s
p
e
c
i
f
ic
t
o
h
o
u
s
eh
o
ld
a
p
p
l
i
an
c
e
s
,
al
o
n
g
w
i
t
h
w
e
a
th
e
r
b
eh
a
v
io
r
d
a
t
a
F
i
g
u
r
e
1
(
s
e
e
A
p
p
en
d
ix
)
.
W
e
c
a
t
eg
o
r
i
z
ed
t
h
e
s
e
p
r
o
p
er
t
i
e
s
i
n
to
t
w
o
d
i
s
t
in
c
t
g
r
o
u
p
s
:
t
h
e
f
ir
s
t
g
r
o
u
p
f
o
cu
s
e
d
o
n
m
o
n
i
t
o
r
i
n
g
w
e
a
t
h
e
r
i
m
p
a
c
t
s
,
w
h
i
le
th
e
s
ec
o
n
d
g
r
o
u
p
c
e
n
t
er
e
d
o
n
m
o
n
it
o
r
i
n
g
t
h
e
e
l
e
c
tr
i
c
i
ty
co
n
s
u
m
p
t
i
o
n
o
f
h
o
u
s
eh
o
ld
a
p
p
l
i
an
c
e
s
T
a
b
l
e
1
.
T
ab
le
1
.
Data
s
et
d
escr
ip
tio
n
S
l
.
N
o
Th
e
c
a
t
e
g
o
r
i
e
s
o
f
f
e
a
t
u
r
e
s
C
h
a
r
a
c
t
e
r
i
s
t
i
c
s
b
e
f
o
r
e
t
h
e
p
r
e
-
p
r
o
c
e
ss
i
n
g
1
To
t
a
l
p
o
w
e
r
c
o
n
s
u
m
p
t
i
o
n
O
v
e
r
a
l
l
,
h
o
m
e
2
H
o
me
a
p
p
l
i
a
n
c
e
s
D
i
sh
w
a
s
h
e
r
M
i
c
r
o
w
a
v
e
Li
v
i
n
g
r
o
o
m
3
W
e
a
t
h
e
r
i
n
f
o
r
m
a
t
i
o
n
Te
mp
e
r
a
t
u
r
e
H
u
mi
d
i
t
y
3.
T
YP
E
S O
F
RE
G
RE
SS
I
O
N
M
O
DE
L
S
3
.
1
.
L
inea
r
r
eg
re
s
s
io
n
L
in
ea
r
r
e
g
r
ess
io
n
is
a
s
tatis
tic
al
m
o
d
elin
g
m
et
h
o
d
th
at
t
r
ies
to
f
ig
u
r
e
o
u
t
t
h
e
r
elatio
n
s
h
ip
b
etwe
en
a
d
ep
en
d
e
n
t
v
ar
iab
le
an
d
as
m
an
y
in
d
ep
e
n
d
en
t
v
a
r
iab
les
as
p
o
s
s
ib
le.
T
h
e
f
ir
s
t
s
tag
e
in
th
e
r
eg
r
ess
io
n
m
o
d
el
th
at
is
u
s
ed
to
m
ak
e
p
r
ed
ictio
n
s
ab
o
u
t
o
u
tco
m
es
is
to
f
in
d
a
lin
k
b
etwe
en
an
in
d
ep
en
d
en
t
v
ar
iab
le
an
d
a
d
ep
en
d
e
n
t
v
ar
ia
b
le.
W
h
en
th
e
r
e
ar
e
a
l
o
t
o
f
in
d
ep
e
n
d
en
t
an
d
d
ep
e
n
d
en
t
v
ar
iab
les,
th
e
m
o
d
el
tr
ies
to
f
ig
u
r
e
o
u
t
h
o
w
a
s
et
o
f
ex
p
lan
at
o
r
y
v
ar
iab
les
an
d
a
r
esp
o
n
s
e
v
a
r
iab
le
ar
e
r
elate
d
t
o
ea
ch
o
th
er
.
I
t is
cu
s
to
m
ar
y
to
u
s
e
m
ea
s
u
r
em
en
ts
lik
e
R
-
s
q
u
ar
ed
an
d
m
ea
n
s
q
u
ar
ed
e
r
r
o
r
(
M
SE)
to
f
in
d
o
u
t
h
o
w
well
th
i
s
lin
ea
r
r
eg
r
ess
io
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
6
9
4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
16
,
No
.
3
,
Sep
tem
b
er
20
25
:
1628
-
1
6
3
6
1630
m
o
d
el
wo
r
k
ed
.
T
h
ese
m
et
r
ics
co
n
v
ey
in
f
o
r
m
atio
n
ab
o
u
t
h
o
w
well
th
e
m
o
d
el
f
its
th
e
d
ata
an
d
h
o
w
well
it
ca
n
ex
p
lain
ev
e
n
ts
b
y
g
iv
i
n
g
th
e
g
o
o
d
n
ess
o
f
f
it a
n
u
m
b
er
.
3
.
2
.
T
he
ra
nd
o
m
f
o
re
s
t
re
g
re
s
s
o
r
T
h
e
r
an
d
o
m
f
o
r
est
r
eg
r
ess
o
r
u
s
es
an
en
s
em
b
le
lear
n
in
g
m
eth
o
d
th
at
m
ix
es
a
lo
t
o
f
d
ec
is
io
n
tr
ee
s
to
m
ak
e
its
p
r
ed
ictio
n
s
m
o
r
e
a
cc
u
r
ate.
C
o
m
b
in
in
g
th
e
p
r
ed
ictio
n
s
o
f
in
d
iv
i
d
u
al
tr
ee
s
is
o
n
e
o
f
th
e
m
o
s
t
s
ig
n
if
ican
t
p
ar
ts
o
f
th
e
r
a
n
d
o
m
f
o
r
est
r
eg
r
ess
o
r
'
s
alg
o
r
ith
m
f
o
r
ad
d
r
ess
in
g
p
r
o
b
lem
s
.
Usi
n
g
a
weig
h
ted
av
er
ag
e
o
f
th
e
p
r
e
d
ictio
n
s
m
ad
e
b
y
ea
ch
d
ec
is
io
n
tr
ee
in
an
en
s
em
b
le
m
ak
es
th
e
f
o
r
ec
ast
m
o
r
e
r
eliab
le
an
d
ac
cu
r
ate.
T
h
e
r
a
n
d
o
m
f
o
r
est
r
eg
r
ess
o
r
is
a
h
an
d
y
t
o
o
l
f
o
r
a
lo
t
o
f
r
eg
r
ess
io
n
p
r
o
b
lem
s
s
in
ce
it
u
s
es
an
en
s
em
b
le
s
tr
ateg
y
t
h
at
h
elp
s
p
r
ev
en
t
o
v
er
f
itti
n
g
an
d
en
c
o
u
r
a
g
es
g
en
er
aliza
tio
n
.
T
h
is
is
b
e
ca
u
s
e
an
e
n
s
em
b
le
m
eth
o
d
m
a
k
es th
in
g
s
m
o
r
e
g
e
n
er
al.
3.
3
.
T
he
g
ra
dient
bo
o
s
t
ing
re
g
re
s
s
o
r
T
h
e
g
r
ad
ien
t
b
o
o
s
tin
g
r
eg
r
ess
o
r
is
an
en
s
em
b
le
lear
n
in
g
m
eth
o
d
t
h
at
u
s
es
a
s
tag
e
-
wis
e
p
r
o
ce
d
u
r
e.
T
h
is
m
eth
o
d
m
ak
es
a
p
r
ed
icti
v
e
m
o
d
el
b
y
co
m
b
i
n
in
g
t
h
e
p
r
ed
ictio
n
s
o
f
wea
k
lear
n
er
s
,
wh
ich
ar
e
g
en
er
ally
d
ec
is
io
n
tr
ee
s
.
G
r
ad
ien
t
b
o
o
s
tin
g
is
a
way
to
s
o
lv
e
p
r
o
b
le
m
s
th
at
r
eq
u
ir
e
f
itti
n
g
n
ew
m
o
d
els
o
n
e
af
ter
th
e
o
th
er
to
f
i
x
th
e
m
is
tak
es
m
ad
e
b
y
th
e
cu
r
r
en
t
e
n
s
em
b
le.
T
h
e
co
n
tr
ib
u
tio
n
s
o
f
ea
ch
m
o
d
el
ar
e
b
ased
o
n
h
o
w
well
th
ey
d
o
,
an
d
t
h
e
f
in
al
f
o
r
ec
ast
is
th
e
weig
h
ted
s
u
m
o
f
all
th
e
co
n
tr
ib
u
tio
n
s
f
r
o
m
th
e
p
r
ec
ed
in
g
m
o
d
els.
B
y
u
s
in
g
th
is
m
eth
o
d
o
n
a
r
e
g
u
lar
b
asis
,
th
e
r
e
m
ain
in
g
m
i
s
tak
es
ar
e
elim
in
ated
,
wh
ich
lead
s
to
a
p
r
e
d
ictio
n
m
o
d
el
th
at
is
ac
cu
r
ate
a
n
d
v
e
r
y
d
ep
e
n
d
ab
le.
3
.
4
.
T
he
s
up
po
rt
v
ec
t
o
r
re
g
re
s
s
o
r
(
SVR)
T
h
e
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
e
(
SVM)
m
o
d
el
is
a
f
lex
ib
le
to
o
l
th
at
ca
n
b
e
u
s
ed
f
o
r
b
o
t
h
cla
s
s
if
icatio
n
an
d
r
eg
r
ess
io
n
.
I
t
h
as
a
n
u
m
b
er
o
f
v
ar
ie
d
u
s
es.
Su
p
p
o
r
t
v
ec
to
r
m
ac
h
in
es
(
SVMs)
ca
n
h
an
d
le
d
ata
th
at
ca
n
b
e
s
ep
ar
ated
in
to
two
o
r
m
o
r
e
g
r
o
u
p
s
,
wh
eth
er
t
h
ey
ar
e
l
in
ea
r
o
r
n
o
t.
T
h
ey
a
r
e
g
r
ea
t
at
wo
r
k
in
g
with
co
m
p
licated
d
atasets
th
at
h
av
e
g
r
o
u
p
s
th
at
ar
e
n
o
t
co
n
n
ec
t
ed
to
ea
ch
o
th
er
.
Su
p
p
o
r
t
v
ec
to
r
m
ac
h
in
es
u
s
e
a
n
u
m
b
er
o
f
k
er
n
els,
s
u
ch
as
s
ig
m
o
id
,
r
ad
ial
b
asis
f
u
n
ctio
n
,
lin
ea
r
,
a
n
d
p
o
ly
n
o
m
ial,
to
tr
an
s
f
o
r
m
in
p
u
t
i
n
to
s
p
ac
es
with
ad
d
itio
n
al
d
im
e
n
s
io
n
s
.
Su
p
p
o
r
t
v
ec
to
r
m
ac
h
in
es,
o
r
SVMs,
ar
e
v
e
r
y
g
o
o
d
at
g
e
n
er
alizin
g
,
av
o
id
in
g
o
v
er
f
itti
n
g
,
an
d
wo
r
k
in
g
well
in
h
ig
h
-
d
im
en
s
io
n
al
s
p
ac
es.
4.
P
E
RF
O
RM
A
NCE
E
VA
L
U
AT
I
O
N
M
E
T
R
I
CS
Fo
r
r
eg
r
ess
io
n
m
o
d
els,
k
ey
m
ea
s
u
r
es
s
u
ch
as
M
SE
an
d
R
-
s
q
u
ar
ed
wer
e
u
tili
ze
d
to
g
au
g
e
th
e
ac
cu
r
ac
y
an
d
p
r
ed
ictiv
e
ca
p
a
b
ilit
y
o
f
th
e
m
o
d
els.
4
.
1
.
M
ea
n
s
qu
a
re
d e
rr
o
r
I
n
r
eg
r
ess
io
n
an
aly
s
is
,
th
e
MSE
is
a
s
tat
is
tic
th
at
is
o
f
ten
u
s
ed
.
I
t
is
th
e
av
er
ag
e
o
f
th
e
s
q
u
ar
ed
d
if
f
er
en
ce
s
b
etwe
en
th
e
e
x
p
ec
ted
v
alu
es
an
d
th
e
v
alu
es
th
at
wer
e
ac
tu
ally
s
ee
n
.
T
h
e
MSE
lo
o
k
s
at
th
e
m
o
s
t
im
p
o
r
tan
t
m
is
tak
es
in
f
o
r
ec
ast
s
to
g
iv
e
a
f
u
ll
p
ictu
r
e
o
f
h
o
w
ac
cu
r
ate
th
ey
ar
e.
T
o
f
in
d
t
h
e
MSE
,
y
o
u
d
iv
id
e
th
e
s
u
m
o
f
t
h
e
s
q
u
ar
e
d
er
r
o
r
s
b
y
th
e
to
tal
n
u
m
b
e
r
o
f
o
b
s
er
v
a
tio
n
s
.
MSE
=
1
n
∑
(
yi
−
yi
̂
k
i
=
1
)
2
(
1
)
4
.
2
.
R
-
s
qu
a
re
d e
rr
o
r
R
-
s
q
u
ar
ed
(
R
²)
,
k
n
o
wn
as
th
e
co
ef
f
icien
t
o
f
d
eter
m
in
atio
n
,
i
s
a
s
tat
is
tical
m
ea
s
u
r
e
u
s
ed
in
r
eg
r
ess
io
n
m
o
d
els
to
s
h
o
w
h
o
w
m
u
ch
th
e
in
d
ep
en
d
en
t
v
ar
iab
les
ex
p
lain
th
e
ch
an
g
es
in
th
e
d
ep
e
n
d
en
t
v
ar
iab
le.
I
n
p
ar
ticu
lar
,
it
s
h
o
ws
h
o
w
well
th
e
m
o
d
el
f
its
th
e
d
ataset
an
d
ch
ec
k
s
h
o
w
well
th
e
m
o
d
el
m
atch
es
th
e
d
ataset.
T
o
f
in
d
th
e
R
2
,
d
iv
id
e
t
h
e
v
ar
i
an
ce
th
at
ca
n
b
e
ex
p
lain
e
d
b
y
th
e
to
tal
v
ar
ian
ce
.
R
2
=
1
−
∑
(
yi
−
yi
̂
k
i
=
1
)
2
∑
(
yi
−
y
̅
i
k
i
=
1
)
2
(
2
)
y
̅
i
-
Actu
al
v
alu
es
T
h
e
f
o
llo
win
g
m
ea
s
u
r
es
ass
ess
th
e
ef
f
ec
tiv
en
ess
o
f
r
eg
r
ess
io
n
m
o
d
els
.
T
h
e
f
o
llo
win
g
m
e
tr
ics
wer
e
u
tili
ze
d
f
o
r
p
e
r
f
o
r
m
an
ce
ev
al
u
atio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
P
r
ed
ictive
ma
ch
in
e
lea
r
n
in
g
f
o
r
s
ma
r
t g
r
id
d
ema
n
d
r
esp
o
n
s
e
a
n
d
efficien
cy
o
p
timiz
a
tio
n
(
J.
C
.
V
in
ith
a
)
1631
5.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
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T
h
e
M
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i
s
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t
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5
1
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6
1
.
A
l
o
w
e
r
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S
E
n
u
m
b
e
r
m
e
a
n
s
t
h
a
t
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h
e
m
o
d
e
l
i
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e
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e
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s
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r
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r
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t
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e
m
o
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h
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s
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u
a
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h
e
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i
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o
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i
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o
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e
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e
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e
n
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e
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a
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Fig
u
r
e
2
.
R
eg
r
ess
io
n
p
l
o
t f
o
r
lin
ea
r
r
eg
r
ess
io
n
Fig
u
r
e
3
s
h
o
ws
th
e
r
an
d
o
m
f
o
r
est
r
eg
r
ess
o
r
with
an
MSE
v
alu
e
o
f
7
8
8
4
.
3
9
.
T
h
is
n
u
m
b
er
is
th
e
av
er
ag
e
o
f
th
e
s
q
u
ar
ed
d
if
f
e
r
e
n
ce
s
b
etwe
en
th
e
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alu
es
th
at
wer
e
ac
tu
ally
s
ee
n
an
d
th
o
s
e
th
at
wer
e
ex
p
ec
ted
.
T
h
e
R
-
s
q
u
ar
ed
s
co
r
e,
wh
ich
is
0
.
5
1
0
5
(
5
1
.
1
%),
s
h
o
ws
h
o
w
well
th
e
m
o
d
el
ca
n
ex
p
lain
ch
an
g
es
in
th
e
d
ep
en
d
e
n
t
v
ar
iab
le.
E
v
e
n
th
o
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g
h
th
e
MSE
is
g
r
ea
ter
,
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I
SS
N
:
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8
8
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4
I
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t J Po
w
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Dr
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t
,
Vo
l.
16
,
No
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3
,
Sep
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20
25
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