I
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l J
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f
E
lect
rica
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ng
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(
I
J
E
CE
)
Vo
l.
15
,
No
.
1
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Feb
r
u
ar
y
20
25
,
p
p
.
46
~
55
I
SS
N:
2088
-
8
7
0
8
,
DOI
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0
.
1
1
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1
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v
15
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1
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pp
46
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55
46
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CC B
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C
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s
p
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A
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:
Gin
as Alv
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in
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Facu
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o
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C
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Un
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lv
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tm
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m
y
1.
I
NT
RO
D
UCT
I
O
N
Fu
el
d
eliv
er
y
b
ec
o
m
es
a
p
r
o
b
lem
wh
en
p
r
o
v
id
in
g
elec
tr
icity
in
r
em
o
te
lo
ca
tio
n
s
.
T
h
e
elec
tr
icity
s
y
s
tem
o
n
is
lan
d
s
o
r
ar
ea
s
with
r
elativ
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lo
w
p
o
p
u
latio
n
d
en
s
ity
is
u
s
u
ally
an
is
o
lated
s
y
s
tem
s
u
p
p
lied
b
y
d
iesel
p
o
wer
p
lan
ts
th
at
u
s
e
m
ar
in
e
f
u
el
o
il
(
MFO)
an
d
h
ig
h
-
s
p
ee
d
d
iesel
(
HSD)
[
1
]
.
Diesel
f
u
el
is
d
eliv
er
ed
to
an
is
o
lated
d
iesel
p
o
wer
p
l
an
t
b
y
tan
k
e
r
tr
u
ck
f
r
o
m
th
e
c
ity
ce
n
ter
.
T
h
is
ca
s
e
r
esu
lts
in
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u
el
s
h
o
r
tag
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d
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el
p
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ices,
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o
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t
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icity
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r
o
u
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t
t
h
e
d
ay
t
o
m
in
im
ize
t
h
e
c
o
s
t
[
2
]
,
[
3
]
.
On
th
e
o
th
er
h
an
d
,
d
i
esel
p
o
wer
p
lan
ts
ar
e
a
f
o
s
s
il
en
er
g
y
s
o
u
r
ce
th
at
co
n
tr
ib
u
tes
to
o
zo
n
e
d
ep
letio
n
,
ac
id
r
ain
,
an
d
g
lo
b
al
war
m
in
g
[
4
]
.
T
h
e
r
ef
o
r
e
,
d
i
v
er
s
if
icatio
n
o
f
en
er
g
y
s
o
u
r
ce
s
is
v
e
r
y
i
m
p
o
r
tan
t,
esp
ec
ially
f
o
r
r
e
n
ewa
b
le
r
eso
u
r
ce
s
.
B
i
o
m
as
s
e
n
e
r
g
y
c
a
n
r
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d
u
c
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d
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p
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n
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c
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o
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l
i
m
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t
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d
a
m
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f
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r
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m
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as
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f
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a
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a
n
d
a
g
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icu
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t
u
r
a
l
wa
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te
.
T
h
e
u
s
e
o
f
b
i
o
m
a
s
s
e
n
e
r
g
y
c
a
n
h
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l
p
s
u
s
t
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i
n
ab
l
e
d
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v
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l
o
p
m
e
n
t
f
o
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c
o
m
m
u
n
i
t
i
e
s
i
n
r
e
m
o
t
e
l
o
ca
t
io
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s
b
y
e
n
s
u
r
i
n
g
a
s
t
a
b
l
e
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ctr
i
c
i
t
y
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u
p
p
l
y
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e
c
a
u
s
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r
e
m
o
te
lo
c
a
t
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o
n
s
o
f
t
e
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h
a
v
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g
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i
f
i
c
a
n
t
b
i
o
m
a
s
s
p
o
t
e
n
t
i
a
l
[
5
]
.
D
i
f
f
e
r
e
n
t
t
y
p
e
s
o
f
b
i
o
m
a
s
s
p
o
t
e
n
ti
a
l
h
a
v
e
d
i
f
f
e
r
e
n
t
p
h
y
s
i
c
a
l
s
t
r
u
ct
u
r
e
s
,
c
h
e
m
i
c
a
l
c
o
m
p
o
s
i
t
i
o
n
s
,
a
n
d
c
a
lo
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i
f
i
c
v
a
l
u
e
s
t
h
a
t
wi
l
l
i
n
f
l
u
e
n
c
e
t
h
e
e
n
e
r
g
y
c
o
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v
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r
s
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o
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p
r
o
c
e
s
s
a
n
d
e
f
f
i
c
i
e
n
c
y
[
6
]
.
Dir
ec
t
co
m
b
u
s
tio
n
,
th
er
m
o
ch
em
ical
p
r
o
ce
s
s
es
(
p
y
r
o
ly
s
is
[
7
]
,
g
asifica
tio
n
,
an
d
d
ir
ec
t
liq
u
ef
ac
tio
n
)
,
an
d
b
io
ch
em
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p
r
o
ce
s
s
es
(
a
n
ae
r
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b
ic
d
ig
esti
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n
an
d
alco
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lic
f
er
m
en
tatio
n
)
ar
e
th
e
th
r
ee
m
ain
way
s
th
at
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
Dete
r
min
a
tio
n
o
f b
io
ma
s
s
en
e
r
g
y
p
o
ten
tia
l b
a
s
ed
o
n
r
eg
io
n
a
l
ch
a
r
a
cteris
tics
…
(
Gin
a
s
A
l
via
n
in
g
s
ih
)
47
b
io
m
ass
is
u
s
ed
.
All
o
f
th
ese
m
eth
o
d
s
tr
a
n
s
f
o
r
m
th
e
b
io
m
ass
in
to
u
s
ef
u
l
p
r
o
d
u
cts
[
8
]
.
B
ec
au
s
e
th
ey
a
r
e
s
u
s
tain
ab
le
an
d
p
o
ten
tially
lo
wer
g
r
ee
n
h
o
u
s
e
g
as
em
is
s
io
n
s
,
th
e
th
er
m
al
co
n
v
er
s
io
n
o
f
b
i
o
m
ass
m
ater
ials
in
to
d
en
s
e
f
u
els
with
a
g
r
ea
ter
ca
lo
r
if
ic
v
alu
e
is
attr
ac
tin
g
atten
tio
n
f
r
o
m
a
r
o
u
n
d
th
e
wo
r
ld
[
9
]
.
So
m
e
r
esear
ch
er
s
h
av
e
f
u
r
th
er
ex
am
i
n
ed
p
lasma
g
asifica
tio
n
tech
n
o
lo
g
y
[
1
0
]
,
[
1
1
]
.
Ma
n
y
b
io
m
ass
p
o
wer
p
l
an
ts
h
av
e
n
o
t
b
ee
n
u
tili
ze
d
o
p
tim
ally
[
1
2
]
b
ec
au
s
e
th
e
s
elec
tio
n
o
f
b
io
m
ass
co
n
v
er
s
io
n
tec
h
n
o
l
o
g
y
d
id
n
o
t
c
o
n
s
id
er
th
e
s
p
ec
if
ic
r
eg
io
n
'
s
ch
ar
ac
ter
is
tics
an
d
t
h
e
co
m
m
o
d
ities
p
r
o
d
u
ce
d
.
T
h
er
ef
o
r
e,
m
ap
p
in
g
th
e
r
eg
io
n
'
s
f
ea
tu
r
es
b
ased
o
n
b
io
m
ass
en
er
g
y
p
o
ten
tial
is
cr
itical
to
im
p
lem
en
tin
g
th
e
b
io
m
ass
p
o
wer
p
lan
t
an
d
ch
o
o
s
in
g
th
e
b
est
co
n
v
er
s
io
n
tec
h
n
o
l
o
g
y
.
Pre
v
io
u
s
s
tu
d
ies
h
av
e
cr
ea
ted
th
e
ap
p
r
o
ac
h
to
esti
m
atin
g
a
n
d
d
eter
m
in
in
g
b
io
m
ass
p
o
ten
tial,
wh
ich
g
en
er
ally
u
s
es
g
eo
s
p
atial
tec
h
n
o
lo
g
y
f
o
r
co
llectin
g
a
n
d
p
r
o
ce
s
s
in
g
d
ata
ab
o
u
t
m
ap
p
in
g
an
ar
ea
[
1
3
]
.
T
h
e
b
io
m
ass
p
o
ten
tial
h
as
b
ee
n
es
tim
ated
b
y
s
tu
d
y
in
g
a
f
ew
g
e
o
s
p
atial
tech
n
o
lo
g
ies
[
1
4
]
–
[
1
6
]
.
C
r
o
p
p
r
o
d
u
ctio
n
s
tatis
t
ics
ca
lcu
late
g
r
o
s
s
b
io
m
ass
p
o
ten
tial
(
GB
P)
in
g
eo
g
r
ap
h
ic
in
f
o
r
m
atio
n
s
y
s
tem
s
(
GI
S)
ap
p
r
o
ac
h
es.
Sp
atio
tem
p
o
r
al
s
atellite
d
ata
p
r
o
d
u
ce
d
g
eo
g
r
ap
h
ic
m
ap
s
o
f
cr
o
p
r
esid
u
e
b
i
o
m
ass
p
o
te
n
tial
u
n
d
e
r
cu
r
r
en
t
co
n
d
itio
n
s
.
R
eg
r
etf
u
lly
,
n
eith
er
th
e
b
i
o
m
ass
s
u
p
p
ly
ch
ai
n
n
o
r
t
h
e
in
ter
ac
tio
n
b
etwe
en
v
ar
iab
les
ca
n
b
e
ac
cu
r
ately
p
r
ed
icted
u
s
in
g
th
is
m
eth
o
d
.
B
ec
au
s
e
o
f
th
is
,
th
e
o
u
tco
m
es
o
f
th
is
ap
p
r
o
ac
h
ar
e
f
r
eq
u
en
tly
s
k
ewe
d
an
d
b
r
o
ad
,
esp
ec
ially
in
ar
ea
s
wh
er
e
lan
d
u
s
e
is
d
ev
elo
p
in
g
q
u
ick
ly
.
I
t
also
tak
es
a
lo
t
o
f
wo
r
k
to
id
en
tif
y
an
d
m
ap
ar
ea
s
with
v
ar
ied
f
ea
tu
r
e
s
,
ad
d
in
g
to
th
e
s
tu
d
y
'
s
co
m
p
l
ex
ity
an
d
len
g
th
an
d
m
ak
in
g
i
t
m
o
r
e
ch
allen
g
in
g
to
esti
m
ate
th
e
b
io
m
ass
p
o
ten
t
ial.
Sev
er
al
p
ar
am
eter
s
,
in
clu
d
in
g
elec
tr
ical
an
d
n
o
n
-
elec
tr
ical
f
ac
to
r
s
s
u
ch
as
b
io
m
ass
ca
lo
r
if
ic
v
alu
e,
am
o
u
n
t
o
f
b
io
m
ass
p
o
ten
tial,
d
em
o
g
r
ap
h
ic
f
ac
t
o
r
s
,
a
n
d
ch
ar
ac
ter
is
tics
o
f
elec
tr
ical
c
o
n
s
u
m
er
s
,
s
h
o
u
ld
b
e
co
n
s
id
er
ed
f
o
r
h
ig
h
-
q
u
ality
b
i
o
m
ass
m
ap
p
in
g
an
d
co
n
v
er
s
i
o
n
tech
n
o
lo
g
y
d
eter
m
in
atio
n
.
T
h
e
au
th
o
r
o
f
t
h
is
jo
u
r
n
al
o
f
f
er
s
a
n
o
v
el
m
eth
o
d
th
at
ca
n
ac
co
m
m
o
d
ate
th
e
b
e
s
t
m
ap
p
in
g
o
f
b
io
m
ass
p
o
ten
t
ial
an
d
co
n
v
er
s
io
n
tech
n
o
lo
g
y
d
eter
m
in
atio
n
u
s
in
g
an
ar
ea
clu
s
ter
izatio
n
.
T
h
e
m
eth
o
d
o
l
o
g
y
en
tails
id
en
tify
in
g
th
e
ar
ea
'
s
d
em
an
d
s
,
f
ea
t
u
r
es,
an
d
p
atter
n
s
b
ased
o
n
b
io
m
ass
p
o
ten
tia
l
b
y
ap
p
l
y
in
g
u
n
s
u
p
er
v
is
ed
l
ea
r
n
in
g
tech
n
iq
u
es
n
am
ed
clu
s
ter
in
g
.
C
lu
s
ter
in
g
is
g
r
o
u
p
i
n
g
r
elate
d
item
s
o
r
r
eg
io
n
s
ac
co
r
d
in
g
to
s
h
a
r
ed
c
h
ar
ac
ter
is
tics
.
Sin
ce
th
e
ad
ap
tiv
e
clu
s
ter
in
g
alg
o
r
ith
m
d
o
esn
'
t
r
eq
u
ir
e
p
r
io
r
k
n
o
w
led
g
e
o
r
lab
elin
g
d
ata
ab
o
u
t
th
e
tar
g
et
g
r
o
u
p
,
it'
s
an
ex
ce
llen
t
o
p
tio
n
f
o
r
m
ap
p
in
g
b
r
o
a
d
ar
ea
s
with
v
ar
io
u
s
p
ar
am
eter
s
.
Mo
d
els
ar
e
f
e
d
u
n
lab
eled
d
ata
t
o
id
en
tify
u
n
d
er
ly
i
n
g
p
atter
n
s
an
d
s
tr
u
ctu
r
es
an
d
g
en
e
r
ate
p
r
ec
is
e
d
ata
clu
s
ter
s
[
1
7
]
.
T
h
e
clu
s
ter
tech
n
iq
u
e
r
ed
u
ce
s
in
f
o
r
m
atio
n
l
o
s
s
wh
ile
s
tan
d
ar
d
izin
g
a
n
d
s
im
p
lify
i
n
g
d
ata
r
ep
r
esen
tatio
n
.
T
h
e
au
th
o
r
o
f
th
is
wo
r
k
h
as
cr
ea
ted
a
clu
s
ter
in
g
m
eth
o
d
o
lo
g
y
u
s
in
g
th
e
f
u
zz
y
C
-
m
e
an
s
(
FC
M)
alg
o
r
ith
m
to
id
en
tify
th
e
en
e
r
g
y
p
o
ten
tial
o
f
b
io
m
ass
b
as
ed
o
n
g
eo
g
r
ap
h
ical
f
ea
tu
r
es
an
d
g
e
n
er
ate
d
ata
clu
s
ter
s
with
a
h
ig
h
d
eg
r
ee
o
f
ac
cu
r
ac
y
.
C
lass
if
y
in
g
r
ea
l
o
r
ab
s
tr
ac
t
item
s
o
r
co
m
p
ar
ab
le
o
b
jects
allo
ws
g
r
o
u
p
in
g
p
r
o
p
er
ties
o
f
clu
s
t
er
in
g
-
b
ased
a
r
ea
s
[
1
8
]
.
As
o
p
p
o
s
ed
t
o
co
m
p
lex
clu
s
ter
i
n
g
tech
n
i
q
u
es
lik
e
K
-
m
ea
n
s
,
ea
ch
p
iece
o
f
d
ata
is
n
o
t g
r
o
u
p
ed
as
a
r
esu
lt.
I
n
p
r
a
ctica
l
s
ce
n
ar
io
s
,
FC
M
p
er
f
o
r
m
s
b
etter
th
an
o
th
e
r
clu
s
ter
in
g
tech
n
iq
u
es
wh
e
n
class
if
y
in
g
d
ata.
T
h
is
tech
n
i
q
u
e
m
ay
ta
k
e
p
ictu
r
es
an
d
ev
alu
ate
b
io
m
ass
's
p
o
ten
tial
b
y
lo
o
k
in
g
at
a
p
la
ce
'
s
p
h
y
s
ical
an
d
p
o
p
u
latio
n
ch
ar
ac
ter
is
tics
.
On
ce
th
e
clu
s
ter
ar
ea
h
as
b
ee
n
d
eter
m
in
ed
,
a
m
o
d
el
ca
n
b
e
c
r
ea
ted
to
id
en
tify
th
e
m
o
s
t
ef
f
ec
tiv
e
tech
n
o
l
o
g
y
f
o
r
co
n
v
er
ti
n
g
b
i
o
m
ass
en
er
g
y
in
to
elec
tr
ical
en
e
r
g
y
.
T
h
is
a
p
p
r
o
ac
h
will
p
r
o
v
id
e
ac
cu
r
ate
m
ap
p
in
g
o
f
th
e
r
eg
io
n
'
s
f
ea
tu
r
es
an
d
e
n
h
an
ce
th
e
d
esig
n
o
f
u
p
co
m
i
n
g
b
i
o
m
ass
p
o
wer
p
lan
ts
with
h
ig
h
er
lev
els
o
f
ef
f
icien
c
y
.
T
h
e
s
tr
u
ctu
r
e
o
f
th
is
p
a
p
er
is
o
u
tlin
ed
as
f
o
llo
ws:
s
ec
tio
n
2
p
r
esen
ts
th
e
r
esear
ch
f
lo
wch
ar
t
an
d
t
h
e
f
u
n
d
am
e
n
tals
o
f
th
e
m
eth
o
d
th
at
will
b
e
u
s
ed
to
im
p
le
m
en
t
th
e
id
ea
an
d
s
tr
ateg
y
o
f
o
p
tim
al
b
i
o
m
ass
m
ap
p
in
g
.
th
is
s
ec
tio
n
also
ela
b
o
r
ates
o
n
th
e
v
a
r
iab
le
th
at
wi
ll
b
e
u
s
ed
as
th
e
i
n
p
u
t.
S
ec
tio
n
3
p
r
esen
ts
th
e
d
ata
an
d
r
esu
lts
o
f
o
u
r
p
r
o
p
o
s
ed
m
eth
o
d
with
v
alid
atio
n
to
d
e
m
o
n
s
tr
ate
its
ef
f
ec
tiv
e
n
ess
.
f
in
ally
,
we
s
u
m
m
ar
ize
o
u
r
f
in
d
in
g
s
in
s
ec
tio
n
4
.
2.
M
E
T
H
O
D
T
h
is
r
esear
ch
u
s
es
m
icr
o
-
s
p
atial
an
aly
s
is
to
ac
q
u
ir
e
im
p
ar
tial
r
esu
lts
u
s
in
g
th
e
m
ac
r
o
-
m
ap
p
i
n
g
tech
n
iq
u
e.
Fig
u
r
e
1
s
h
o
ws
t
h
e
r
esear
ch
f
lo
wch
ar
t.
T
h
e
m
eth
o
d
o
l
o
g
y
u
s
ed
in
c
o
n
d
u
c
tin
g
th
is
s
tu
d
y
ca
n
g
en
er
ally
b
e
d
iv
id
ed
in
t
o
5
p
ar
ts
:
th
e
p
r
elim
in
ar
y
wo
r
k
,
ar
ea
clu
s
ter
izatio
n
,
clu
s
ter
v
alid
atio
n
,
clu
s
ter
r
esu
lt
m
ap
p
in
g
,
an
d
r
eg
io
n
al
c
h
ar
ac
ter
is
tic
an
aly
s
is
.
T
h
e
p
r
elim
in
ar
y
wo
r
k
co
n
tain
s
th
e
liter
atu
r
e
s
tu
d
y
,
v
ar
iab
le
d
ec
is
io
n
,
an
d
d
ata
co
llectio
n
.
T
h
e
p
o
ten
tial
b
io
m
ass
o
f
1
6
4
s
u
b
d
is
tr
icts
in
a
p
r
o
v
in
ce
is
ca
lcu
lated
in
th
is
ar
ticle.
T
o
ch
o
o
s
e
th
e
b
est
co
n
v
e
r
s
io
n
tech
n
o
lo
g
y
,
s
ev
er
al
f
ac
to
r
s
i
n
clu
d
e
elec
tr
ical
an
d
n
o
n
-
elec
tr
ic
attr
ib
u
t
es
u
n
iq
u
e
to
ea
ch
s
u
b
d
is
tr
ict.
T
h
e
v
ar
iab
les
co
n
s
id
er
ed
f
o
r
th
is
in
v
esti
g
atio
n
ar
e
lis
ted
in
T
ab
le
1
.
T
h
e
s
u
b
d
is
tr
ict's
p
o
p
u
latio
n
,
p
lan
tatio
n
s
,
ag
r
icu
ltu
r
e,
an
d
a
n
n
u
al
p
r
o
d
u
ctio
n
ar
e
e
x
am
p
le
s
o
f
n
o
n
-
elec
tr
ical
c
h
ar
ac
ter
is
tics
.
T
h
e
elec
tr
ical
v
ar
iab
les
ar
e
th
e
in
s
talled
ca
p
ac
ity
,
elec
tr
ical
en
e
r
g
y
s
o
ld
,
th
e
n
u
m
b
e
r
o
f
elec
tr
ical
c
o
n
s
u
m
er
s
,
an
d
th
e
ca
p
ac
ity
an
d
r
u
n
n
in
g
h
o
u
r
s
o
f
th
e
is
o
lated
d
iesel
p
o
wer
p
la
n
t.
T
h
e
cr
o
p
ty
p
es
co
n
s
id
er
ed
co
m
m
o
d
ities
in
th
e
p
r
o
v
in
ce
in
clu
d
e
p
alm
o
il,
c
o
c
o
n
u
t,
r
u
b
b
e
r
,
co
f
f
ee
,
c
o
co
a,
ar
ec
a
n
u
t,
s
ag
o
,
an
d
r
ice.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
1
,
Feb
r
u
ar
y
20
25
:
46
-
55
48
Fig
u
r
e
1
.
R
esear
ch
f
lo
wc
h
ar
t
T
ab
le
1
.
E
lectr
ical
an
d
n
o
n
-
el
ec
tr
ical
v
ar
iab
les
P
o
p
u
l
a
t
i
o
n
a
n
d
d
e
mo
g
r
a
p
h
y
P
l
a
n
t
a
t
i
o
n
a
n
d
a
g
r
i
c
u
l
t
u
r
e
El
e
c
t
r
i
c
i
t
y
W
i
d
e
o
f
t
h
e
a
r
e
a
(
k
m
2
)
W
i
d
e
o
f
p
l
a
n
t
a
t
i
o
n
(
h
a
)
I
n
st
a
l
l
e
d
c
a
p
a
c
i
t
y
(
V
A
)
R
e
si
d
e
n
t
p
o
p
u
l
a
t
i
o
n
(
t
h
o
u
s
a
n
d
p
e
o
p
l
e
)
A
n
n
u
a
l
p
r
o
d
u
c
t
i
o
n
(
t
o
n
s)
El
e
c
t
r
i
c
a
l
e
n
e
r
g
y
s
o
l
d
(
k
W
h
)
N
u
mb
e
r
o
f
e
l
e
c
t
r
i
c
a
l
c
o
n
su
m
e
r
s
2
.
1
.
Ada
ptiv
e
clus
t
er
ing
B
ased
o
n
lan
d
u
s
e
s
im
u
latio
n
m
o
d
elin
g
,
m
icr
o
-
s
p
atial
an
aly
s
is
is
an
ar
ea
an
aly
s
is
th
a
t
s
tar
ts
b
y
s
eg
m
en
tin
g
th
e
r
e
g
io
n
in
to
s
m
aller
ar
ea
s
[
1
9
]
,
[
2
0
]
.
T
h
er
e
ar
e
two
ty
p
es
o
f
clu
s
ter
in
g
,
n
am
ely
h
ar
d
clu
s
ter
in
g
an
d
s
o
f
t
clu
s
ter
in
g
.
Har
d
cl
u
s
ter
in
g
an
d
s
o
f
t
clu
s
ter
in
g
ar
e
th
e
two
d
if
f
er
en
t
f
o
r
m
s
o
f
clu
s
ter
in
g
.
Har
d
clu
s
ter
in
g
en
tails
co
u
n
tin
g
th
e
n
u
m
b
e
r
o
f
cl
u
s
ter
s
s
eq
u
en
tially
,
b
eg
in
n
in
g
with
th
e
s
m
allest
n
u
m
b
er
.
A
clu
s
ter
v
alid
atio
n
ap
p
r
o
ac
h
is
th
e
n
u
s
ed
to
ass
ess
th
e
clu
s
ter
in
g
p
er
f
o
r
m
an
ce
m
an
u
ally
.
C
o
n
v
er
s
ely
,
s
o
f
t
clu
s
ter
in
g
,
wh
ich
is
o
f
ten
r
ef
e
r
r
ed
t
o
a
s
ad
ap
tiv
e
clu
s
ter
in
g
,
is
an
alg
o
r
ith
m
th
at,
b
y
a
n
aly
zin
g
clu
s
ter
o
u
tco
m
es,
au
to
m
atica
lly
g
en
er
ates
d
ata
g
r
o
u
p
in
g
with
th
e
m
a
x
im
u
m
n
u
m
b
er
o
f
clu
s
ter
s
.
So
f
t
clu
s
ter
in
g
is
a
s
u
p
er
io
r
m
eth
o
d
s
in
ce
it m
o
r
e
ap
p
r
o
p
r
i
ately
ca
p
tu
r
es th
e
co
n
d
itio
n
o
f
th
e
d
ata
an
d
th
e
co
r
r
elatio
n
s
b
etwe
en
v
ar
iab
les.
T
h
is
s
tu
d
y
is
n
ew
b
ec
au
s
e
it
u
s
es
ad
ap
tiv
e
clu
s
ter
in
g
tech
n
iq
u
es.
T
h
is
tech
n
i
q
u
e
is
c
h
o
s
e
n
b
ec
au
s
e,
b
ased
o
n
th
e
a
n
aly
s
is
o
f
clu
s
ter
r
esu
lts
,
th
is
alg
o
r
ith
m
ca
n
au
to
m
atica
lly
b
u
ild
d
ata
g
r
o
u
p
s
with
th
e
id
ea
l
n
u
m
b
er
o
f
clu
s
ter
s
.
T
h
is
is
n
o
t
th
e
ca
s
e
with
th
e
tr
ad
iti
o
n
al
clu
s
ter
in
g
tech
n
iq
u
e,
w
h
ich
clu
s
ter
s
d
ata
s
eq
u
en
tially
o
r
r
an
d
o
m
ly
,
s
tar
tin
g
with
th
e
f
ewe
s
t
p
o
s
s
ib
le
clu
s
ter
s
.
Su
b
s
eq
u
en
tly
,
th
e
clu
s
ter
v
alid
atio
n
ap
p
r
o
ac
h
is
em
p
lo
y
e
d
to
an
aly
ze
its
p
er
f
o
r
m
a
n
ce
p
er
s
o
n
ally
.
C
o
n
v
e
n
tio
n
al
cl
u
s
ter
te
ch
n
iq
u
es
a
r
e
m
o
r
e
ex
ten
d
ed
an
d
less
ef
f
icien
t.
T
h
e
u
s
e
o
f
u
n
clea
r
C
-
m
ea
n
s
o
f
ten
allo
ws
f
o
r
s
o
f
t
clu
s
ter
in
g
.
FC
M.
T
h
e
FC
M
alg
o
r
ith
m
is
as
[
2
1
]
:
a.
Data
X
n
ee
d
s
to
b
e
en
ter
ed
as
a
m
atr
ix
with
a
d
im
en
s
i
o
n
o
f
×
,
wh
er
e
p
is
ea
ch
d
ata
s
am
p
le'
s
ch
ar
ac
ter
is
tic
an
d
n
is
th
e
to
tal
n
u
m
b
e
r
o
f
d
ata
s
am
p
les.
=
d
ata
s
am
p
le
−
ℎ
(
=
1
,
2
,
…
,
)
,
d
ata
attr
ib
u
te
−
ℎ
(
=
1
,
2
,
3
,
…
,
).
b.
E
s
tab
lis
h
th
e
g
o
al
f
u
n
ctio
n
,
i
n
itial
iter
atio
n
,
m
a
x
im
u
m
iter
atio
n
,
ex
p
ec
ted
er
r
o
r
,
weig
h
ti
n
g
p
o
wer
,
a
n
d
n
u
m
b
er
o
f
cl
u
s
ter
s
.
c.
As ele
m
en
ts
o
f
th
e
f
ir
s
t p
ar
titi
o
n
m
atr
ix
,
g
en
e
r
ate
a
r
an
d
o
m
n
u
m
b
er
(
,
=
1
,
2
.
.
.
,
;
=
1
,
2
,
…
,
).
0
=
[
11
(
1
)
12
(
2
)
⋯
1
(
)
⋮
⋮
0
⋮
11
(
1
)
12
(
2
)
⋯
1
(
)
]
(
1
)
I
n
f
u
zz
y
clu
s
ter
in
g
,
th
e
p
ar
titi
o
n
m
atr
ix
n
ee
d
s
to
f
u
lf
ill th
e
s
u
b
s
eq
u
en
t r
eq
u
ir
em
e
n
ts
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
Dete
r
min
a
tio
n
o
f b
io
ma
s
s
en
e
r
g
y
p
o
ten
tia
l b
a
s
ed
o
n
r
eg
io
n
a
l
ch
a
r
a
cteris
tics
…
(
Gin
a
s
A
l
via
n
in
g
s
ih
)
49
=
[
0
,
1
]
;
(
1
≤
≤
;
1
≤
≤
)
∑
=
1
=
1
;
1
≤
≤
ℎ
0
<
∑
=
1
<
;
1
≤
≤
(
2
)
Dete
r
m
in
e
an
d
ascer
tain
ea
c
h
co
lu
m
n
'
s
(
attr
ib
u
te'
s
)
q
u
an
tity
:
=
∑
=
1
(
3
)
wh
er
e
=
1
,
2
,
3
,
…
, m
,
th
e
n
d
eter
m
in
e
ea
ch
d
ata'
s
d
eg
r
ee
o
f
m
em
b
er
s
h
ip
=
(
4
)
d.
Dete
r
m
in
e
th
e
k
-
cl
u
s
ter
'
s
clu
s
t
er
ce
n
tr
o
id
:
,
wh
er
e
=
1
,
2
,
3
,
…
,
an
d
=
1
,
2
,
3
,
…
,
=
∑
(
(
)
∗
)
=
1
∑
(
)
=
1
(
5
)
=
[
11
⋯
1
⋮
⋱
⋮
1
⋯
]
e.
C
alcu
late
th
e
o
b
jectiv
e
f
u
n
ctio
n
,
=
∑
∑
(
[
∑
(
−
)
2
=
1
]
(
)
)
=
1
=
1
(
6
)
f.
C
alcu
late
th
e
p
ar
titi
o
n
m
atr
ix
ch
an
g
e:
=
[
∑
(
−
)
2
=
1
]
−
1
−
1
∑
[
∑
(
−
)
2
=
1
]
−
1
−
1
=
1
(
7
)
g.
Ver
if
y
th
e
s
to
p
c
o
n
d
itio
n
:
−
I
t is f
in
is
h
ed
if
(
|
−
−
1
|
<
)
o
r
(
<
)
−
I
f
n
o
t,
g
o
b
ac
k
to
s
tep
d
with
=
+
1
.
2
.
2
.
I
nd
ex
o
f
clus
t
er
v
a
lid
a
t
io
n
T
h
e
clu
s
ter
v
alid
atio
n
in
d
e
x
(
C
VI
)
is
o
n
e
to
o
l
f
o
r
ev
alu
ati
n
g
a
clu
s
ter
'
s
q
u
ality
an
d
s
tr
e
n
g
th
[
2
2
]
.
T
h
e
o
p
tim
u
m
clu
s
ter
o
u
tco
m
e
is
in
f
lu
e
n
ce
d
b
y
th
e
clu
s
ter
m
eth
o
d
,
d
ata
s
et
p
r
o
p
er
ties
,
d
ata
s
ize,
n
u
m
b
er
o
f
clu
s
ter
s
u
s
ed
,
an
d
d
ata
s
tr
u
ct
u
r
e.
As
a
r
esu
lt,
C
VI
is
cr
u
cial
f
o
r
ass
ess
in
g
th
e
clu
s
ter
'
s
q
u
ality
.
T
h
er
e
ar
e
m
an
y
tech
n
iq
u
es
f
o
r
C
VI
,
in
clu
d
in
g
th
e
Du
n
n
in
d
ex
[
2
3
]
,
[
2
4
]
,
th
e
Dav
ies
-
B
o
u
ld
in
s
co
r
e,
th
e
C
alin
s
k
i
-
Har
ab
asz
s
co
r
e,
an
d
t
h
e
Sil
h
o
u
ette
in
d
e
x
.
T
wo
C
VI
ar
e
m
e
n
tio
n
ed
in
a
f
ew
liter
ar
y
wo
r
k
s
[
2
5
]
,
[
2
6
]
.
I
n
th
is
ca
s
e,
th
e
v
alid
ity
tech
n
iq
u
e
u
s
ed
is
th
e
Sil
h
o
u
ette
in
d
ex
,
also
k
n
o
wn
as
th
e
Kello
g
g
-
Sil
h
o
u
ette
in
d
ex
.
C
o
m
b
in
in
g
th
e
co
h
esio
n
m
eth
o
d
,
wh
ich
in
v
o
lv
es
an
aly
zin
g
d
ata
with
in
a
clu
s
ter
,
with
th
e
s
ep
ar
atio
n
m
eth
o
d
,
wh
ich
d
et
er
m
in
es
th
e
r
elatio
n
s
h
ip
b
etwe
en
th
e
o
u
tco
m
es
o
f
th
o
s
e
clu
s
ter
s
,
r
esu
lts
in
th
e
s
ilh
o
u
ette
co
ef
f
icien
t
m
eth
o
d
.
T
h
e
av
er
ag
e
b
etwe
en
a
n
o
b
je
ct
an
d
ev
er
y
o
t
h
er
o
b
ject
in
th
e
s
am
e
clu
s
ter
an
d
o
b
jects
in
d
i
f
f
er
en
t
clu
s
ter
s
ca
n
b
e
d
eter
m
in
e
d
b
y
a
p
p
ly
i
n
g
th
e
Sil
h
o
u
ette
al
g
o
r
ith
m
[
2
7
]
.
E
v
er
y
g
r
o
u
p
'
s
s
ilh
o
u
ette
is
p
lo
tted
to
co
m
p
a
r
e
th
e
q
u
ality
o
f
c
o
n
tr
ib
u
tio
n
s
b
ased
o
n
th
e
s
ilh
o
u
ettes'
ar
ea
(
o
r
lig
h
t
len
g
t
h
)
.
T
h
e
s
ilh
o
u
ette
co
ef
f
icien
t c
an
b
e
ca
lcu
lated
u
s
in
g
t
h
e
eq
u
atio
n
th
at
f
o
llo
ws:
(
)
=
(
)
−
(
)
m
ax
(
(
)
,
(
)
(
8
)
wh
er
e
(
)
=
v
alu
e
o
f
s
ilh
o
u
ette
co
ef
f
icien
t
(
)
=
av
er
ag
e
d
is
tan
ce
o
f
i
-
d
ata
(
)
=
av
er
ag
e
d
is
tan
ce
o
f
i
-
d
ata
w
ith
all
m
em
b
er
s
T
h
e
s
ilh
o
u
ette
wid
th
in
d
ex
is
u
s
ed
to
in
ter
p
r
et
s
ilh
o
u
ette
v
al
u
e,
as in
d
icate
d
in
T
ab
le
2
[
2
1
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
1
,
Feb
r
u
ar
y
20
25
:
46
-
55
50
T
ab
le
2
.
Sil
h
o
u
ette
wid
th
in
d
e
x
[
2
1
]
S
i
l
h
o
u
e
t
t
e
c
o
e
f
f
i
c
i
e
n
t
I
n
t
e
r
p
r
e
t
a
t
i
o
n
b
e
t
w
e
e
n
o
b
j
e
c
t
s
a
n
d
g
r
o
u
p
s f
o
r
me
d
0
.
7
<
S
C
<
1
S
t
r
o
n
g
st
r
u
c
t
u
r
e
0
.
5
<
S
C
<
0
.
7
M
e
d
i
u
m s
t
r
u
c
t
u
r
e
0
.
2
5
<
S
C
<
0
.
5
W
e
a
k
st
r
u
c
t
u
r
e
S
C
<
0
.
2
5
N
o
r
e
l
a
t
i
o
n
2
.
3
.
Clus
t
er
ing
in bio
m
a
s
s
m
a
pp
ing
W
h
en
a
v
ast
q
u
an
tity
an
d
v
ar
iety
o
f
g
eo
g
r
a
p
h
ic
d
ata
is
av
ailab
le,
s
am
p
lin
g
a
r
eg
io
n
with
n
u
m
er
o
u
s
f
r
eq
u
e
n
tly
co
n
n
ec
ted
p
ar
a
m
eter
s
is
d
o
n
e
to
h
elp
.
T
h
e
ap
p
licatio
n
p
r
o
ce
s
s
is
ca
r
r
ied
o
u
t
af
ter
a
clu
s
ter
is
co
n
s
tr
u
cted
to
c
o
n
n
ec
t
d
ata
wi
th
d
if
f
er
e
n
t
lo
ca
tio
n
s
,
af
te
r
wh
ich
it
is
co
n
n
ec
ted
a
n
d
a
n
aly
z
ed
,
an
d
f
in
ally
,
t
h
e
r
esu
lts
ar
e
r
ep
o
r
ted
.
Sp
atial
d
ata
m
u
s
t
b
e
p
r
o
ce
s
s
ed
to
p
r
o
d
u
ce
s
p
atially
an
d
tem
p
o
r
ally
o
r
i
en
ted
d
ata
th
at
ca
n
b
e
u
s
ed
as a
r
ef
e
r
en
ce
s
y
s
tem
.
Data
p
r
o
p
e
r
ties
f
o
r
s
p
atial
d
a
ta
an
d
p
lo
ttin
g
,
s
u
ch
as
to
p
o
g
r
ap
h
y
an
d
lan
d
z
o
n
es
o
n
m
a
p
s
,
ca
n
b
e
cu
s
to
m
ized
with
b
io
m
ass
m
a
p
p
in
g
.
Ad
d
itio
n
ally
,
it
is
p
o
s
s
ib
le
to
m
i
x
s
p
atial
d
ata
with
o
th
er
s
p
atial
d
ata
to
cr
ea
te
a
co
m
p
lem
en
tar
y
d
ata
lay
er
.
T
ec
h
n
ical
s
tan
d
ar
d
s
s
u
ch
as
m
ap
p
r
o
jectio
n
s
y
s
tem
s
an
d
ty
p
es
o
f
lay
e
r
s
ar
e
r
eq
u
i
r
ed
to
en
s
u
r
e
t
h
e
r
eliab
ilit
y
o
f
g
e
o
g
r
ap
h
ic
in
f
o
r
m
atio
n
s
y
s
tem
s
.
T
h
ese
s
p
ee
d
s
u
p
th
e
n
ee
d
f
o
r
b
io
m
ass
m
ap
p
in
g
an
d
b
io
m
ass
p
o
wer
p
la
n
t p
lan
n
i
n
g
.
2
.
4
.
Reg
i
o
na
l
cha
ra
ct
er
iza
t
i
o
n
R
eg
io
n
al
ch
ar
ac
ter
izatio
n
d
et
er
m
in
atio
n
f
o
r
ea
c
h
clu
s
ter
w
ill
b
e
d
o
n
e
u
s
in
g
c
o
r
r
elatio
n
t
ec
h
n
iq
u
es.
E
ac
h
clu
s
ter
m
e
m
b
er
will
h
a
v
e
th
e
ex
ac
t
r
eg
io
n
al
ch
ar
ac
t
er
izatio
n
.
T
h
e
co
r
r
elatio
n
co
e
f
f
icien
t
b
etwe
en
th
e
wid
th
o
f
t
h
e
p
la
n
tatio
n
an
d
th
e
to
tal
ar
ea
ca
n
an
aly
ze
th
e
m
o
s
t
b
io
m
ass
p
o
ten
tial
in
a
clu
s
ter
.
T
h
is
ap
p
r
o
ac
h
will m
ak
e
th
e
d
ata
ea
s
ier
to
u
n
d
er
s
tan
d
an
d
p
r
o
v
id
e
u
s
er
s
with
m
o
r
e
r
elev
an
t in
f
o
r
m
atio
n
.
T
h
e
co
r
r
elatio
n
co
ef
f
icien
t,
d
en
o
ted
b
y
,
m
ea
s
u
r
es
th
e
s
tr
en
g
th
o
f
th
e
s
tr
aig
h
t
-
lin
e
o
r
lin
ea
r
r
elatio
n
s
h
ip
b
etwe
en
two
v
ar
i
ab
les
[
2
8
]
.
T
h
e
f
o
llo
win
g
p
o
i
n
ts
ar
e
th
e
ac
ce
p
ted
g
u
id
elin
e
s
f
o
r
in
ter
p
r
etin
g
th
e
co
r
r
elatio
n
c
o
ef
f
icien
t:
−
0
in
d
icate
s
n
o
lin
ea
r
r
elatio
n
s
h
ip
.
−
+1
in
d
icate
s
a
p
e
r
f
ec
t
p
o
s
itiv
e
lin
ea
r
r
elatio
n
s
h
ip
–
as
o
n
e
v
ar
iab
le
i
n
cr
ea
s
es
in
its
v
alu
es,
th
e
o
th
er
in
cr
ea
s
es th
r
o
u
g
h
an
e
x
ac
t lin
ea
r
r
u
le.
−
−1
in
d
icate
s
a
p
er
f
ec
t
n
eg
ati
v
e
lin
ea
r
r
elatio
n
s
h
ip
–
as
o
n
e
v
ar
ia
b
le
in
cr
ea
s
es
in
its
v
alu
es,
th
e
o
th
e
r
d
ec
r
ea
s
es th
r
o
u
g
h
an
e
x
ac
t lin
ea
r
r
u
le.
−
Valu
es
b
etwe
en
0
a
n
d
0
.
3
(
0
an
d
−0
.
3
)
i
n
d
icate
a
wea
k
p
o
s
itiv
e
(
n
eg
ativ
e)
lin
ea
r
r
elatio
n
s
h
ip
th
r
o
u
g
h
a
s
h
ak
y
lin
ea
r
r
u
le.
−
Valu
es
b
etwe
en
0
.
3
an
d
0
.
7
(
0
.
3
an
d
−0
.
7
)
in
d
icate
a
m
o
d
er
ate
p
o
s
itiv
e
(
n
eg
ativ
e)
lin
ea
r
r
elatio
n
s
h
ip
th
r
o
u
g
h
a
f
u
zz
y
-
f
ir
m
lin
ea
r
r
u
l
e.
−
Valu
es
b
etwe
en
0
.
7
an
d
1
.
0
(
−0
.
7
an
d
−
1
.
0
)
i
n
d
icate
a
s
tr
o
n
g
p
o
s
itiv
e
(
n
eg
ativ
e
)
lin
ea
r
r
elatio
n
s
h
ip
th
r
o
u
g
h
a
f
ir
m
lin
ea
r
r
u
le.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
Da
t
a
T
ab
les 3
to
5
s
h
o
w
d
ata
th
at
in
clu
d
e
th
e
v
ar
ia
b
les u
s
ed
.
T
h
e
1
6
4
d
ata
u
s
ed
in
th
is
r
esear
ch
s
h
o
w
o
n
ly
f
iv
e
s
u
b
d
is
tr
icts
.
T
h
e
d
ata
n
ee
d
s
to
b
e
n
o
r
m
alize
d
b
e
f
o
r
e
th
e
clu
s
ter
in
g
p
r
o
ce
s
s
ca
n
b
e
g
i
n
.
No
r
m
aliza
tio
n
is
ess
en
tial
to
ar
r
an
g
e
th
e
q
u
alities
o
f
d
if
f
er
e
n
t
en
titi
es
in
to
a
h
elp
f
u
l
co
n
n
ec
tio
n
s
tr
u
ctu
r
e
(
with
o
u
t
r
ed
u
n
d
an
c
y
o
r
d
ata
r
e
p
etitio
n
)
.
T
h
is
p
r
o
ce
s
s
will r
em
o
v
e
th
e
m
ajo
r
ity
o
f
th
e
am
b
ig
u
ity
.
T
h
e
d
ata
p
lo
t
c
o
m
p
a
r
is
o
n
in
Fig
u
r
e
2
d
em
o
n
s
tr
ates
th
e
s
u
b
s
tan
tial
im
p
ac
t
o
f
th
e
n
o
r
m
aliza
tio
n
p
r
o
ce
d
u
r
e
o
n
th
e
d
ata.
Sin
ce
th
e
r
aw
d
ata
ar
e
n
o
t
d
is
p
er
s
ed
eq
u
ally
at
s
o
m
e
p
o
in
t
,
it
is
cle
ar
f
r
o
m
th
e
p
lo
t
o
f
th
e
ac
tu
al
d
ata
in
Fig
u
r
e
2
(
a)
th
at
th
er
e
is
f
r
eq
u
e
n
t
u
n
ce
r
tai
n
ty
in
th
e
r
esu
lts
.
Ho
wev
e
r
,
a
f
ter
n
o
r
m
alizin
g
th
e
d
ata
d
is
p
lay
ed
in
Fig
u
r
e
2
(
b
)
,
th
e
d
is
tr
ib
u
tio
n
o
f
th
e
n
o
r
m
ali
ze
d
d
ata
f
o
r
m
s
a
s
tr
aig
h
tf
o
r
w
ar
d
,
n
o
n
-
r
ed
u
n
d
a
n
t
en
tity
,
g
u
ar
a
n
teein
g
t
h
at
th
e
d
ata
is
o
f
h
ig
h
q
u
ality
f
o
r
th
e
s
u
b
s
eq
u
en
t stag
e.
T
ab
le
3
.
Po
p
u
latio
n
an
d
d
em
o
g
r
ap
h
y
v
ar
ia
b
les
S
u
b
-
d
i
s
t
r
i
c
t
(
G
r
i
d
)
W
i
d
e
o
f
t
h
e
a
r
e
a
(
k
m
2
)
R
e
si
d
e
n
t
p
o
p
u
l
a
t
i
o
n
(
t
h
o
u
s
a
n
d
p
e
o
p
l
e
)
K
u
a
n
t
a
n
M
u
d
i
k
5
6
4
.
28
25
.
83
H
u
l
u
K
u
a
n
t
a
n
3
8
4
.
40
9
.
55
G
u
n
u
n
g
To
a
r
1
6
5
,
2
5
14
.
20
P
u
c
u
k
R
a
n
t
a
u
8
2
1
.
64
10
.
54
S
i
n
g
i
n
g
i
1
,
9
5
3
.
66
35
.
43
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51
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.
Plan
tatio
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f
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s
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r
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P
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W
i
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p
l
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t
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(
h
a
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n
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t
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31
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36
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u
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51
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u
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r
8
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88
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.
E
lectr
ical
p
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r
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eter
s
S
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r
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El
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s
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u
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M
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k
20
,
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6
8
7
,
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1
5
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u
l
u
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u
a
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t
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,
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7
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9
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u
n
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To
a
r
12
,
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u
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a
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37
,
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(
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u
r
e
2
.
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o
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p
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r
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e
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ata
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o
r
(
a)
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t
u
al
d
ata
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d
(
b
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ata
3
.
2
.
Clus
t
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ing
re
s
ult
a
nd
v
a
lid
a
t
io
n
T
o
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eter
m
in
e
t
h
e
id
ea
l
n
u
m
b
e
r
o
f
clu
s
ter
s
,
u
s
e
ad
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tiv
e
clu
s
ter
in
g
b
ased
o
n
th
e
s
ilh
o
u
ette
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o
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ith
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an
d
FC
M
tech
n
iq
u
es.
T
h
is
p
r
o
ce
d
u
r
e
r
eq
u
i
r
es
in
p
u
t,
t
h
e
f
i
n
al
iter
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,
th
e
m
ax
im
u
m
er
r
o
r
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th
e
lo
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d
h
ig
h
est
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o
s
s
ib
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m
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er
o
f
cl
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ter
s
,
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d
th
e
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o
r
m
alize
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d
at
a
.
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h
e
clu
s
ter
in
g
alg
o
r
ith
m
s
o
r
g
an
ize
t
h
e
d
ata
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to
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m
in
im
al
n
u
m
b
er
o
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g
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p
s
u
s
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ad
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ter
in
g
a
n
d
c
o
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tin
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e
u
n
til
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e
m
ax
im
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m
n
u
m
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er
is
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lis
h
ed
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th
e
f
ir
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t
s
tep
s
.
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t,
s
ilh
o
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ette
ap
p
r
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h
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ar
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ed
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a
s
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es
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e
o
u
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o
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ch
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u
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ter
in
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alg
o
r
ith
m
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s
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er
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o
r
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ce
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e
o
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tim
u
m
s
ilh
o
u
ette
in
d
e
x
is
s
elec
ted
to
ac
q
u
ir
e
th
e
o
p
tim
al
q
u
a
n
tity
o
f
c
lu
s
ter
s
.
Fig
u
r
e
3
d
is
p
lay
s
th
e
o
u
tco
m
es
o
f
clu
s
ter
in
g
r
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lts
an
d
v
alid
atio
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.
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ac
h
n
u
m
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er
o
f
th
e
clu
s
ter
'
s
s
ilh
o
u
ette
in
d
ex
is
d
is
p
lay
ed
.
Fro
m
th
e
4
e
x
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er
im
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ts
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n
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cted
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was
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o
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h
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est
Sil
h
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ex
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a
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ter
n
u
m
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e
r
o
f
4
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h
e
v
alu
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s
h
o
ws
h
o
w
th
e
cr
ea
ted
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s
ter
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d
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u
b
-
d
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icts
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e
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ter
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ete
d
.
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h
e
s
u
b
d
is
tr
ict
is
s
ep
ar
ated
f
r
o
m
o
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er
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r
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u
p
s
p
r
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d
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ce
d
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y
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e
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ce
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t
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o
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ette
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icien
t
v
alu
e
n
ea
r
+1
.
T
h
e
g
r
id
is
at
o
r
r
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s
o
n
ab
ly
n
ea
r
t
h
e
d
ec
is
io
n
b
o
r
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er
o
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th
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g
r
id
if
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r
th
is
0
.
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g
r
id
s
h
o
u
ld
b
e
in
a
s
ep
a
r
ate
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s
ter
if
its
v
alu
e
is
m
o
r
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h
ar
m
f
u
l,
wh
ich
s
u
g
g
ests
th
at
th
e
g
r
id
o
v
er
la
p
s
.
As
s
h
o
w
n
in
Fig
u
r
e
3
,
t
h
e
s
ilh
o
u
ette
co
ef
f
icien
t
h
as
a
m
ea
n
v
alu
e
o
f
0
.
7
.
T
a
b
le
2
in
d
i
ca
tes
th
at
th
e
s
ilh
o
u
ette
v
alu
e
is
h
ig
h
er
th
a
n
0
.
7
,
in
d
icatin
g
a
s
o
lid
s
tr
u
ctu
r
e
d
e
v
elo
p
ed
b
etwe
en
th
e
item
s
.
T
a
b
le
6
s
h
o
ws
th
e
to
tal
n
u
m
b
er
o
f
m
em
b
e
r
s
o
f
ea
ch
clu
s
ter
.
C
lu
s
ter
1
,
with
1
3
6
s
u
b
-
d
is
tr
icts
,
o
r
8
2
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%
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th
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s
u
b
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icts
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am
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ed
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as
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h
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m
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ig
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if
ican
t
n
u
m
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er
o
f
m
em
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.
C
lu
s
ter
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2
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a
n
d
4
co
n
s
is
t o
f
4
,
9
,
a
n
d
1
2
s
u
b
-
d
is
tr
icts
,
r
esp
ec
tiv
ely
.
T
o
v
e
r
if
y
th
at
f
o
u
r
clu
s
ter
s
ar
e
th
e
i
d
ea
l
n
u
m
b
er
to
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ild
,
v
alid
atio
n
u
s
in
g
th
e
s
ilh
o
u
ette
ap
p
r
o
ac
h
is
d
o
n
e
u
s
in
g
(
8
)
;
Fig
u
r
e
4
d
is
p
lay
s
th
e
o
u
tco
m
es
o
f
clu
s
ter
v
alid
atio
n
.
E
ac
h
s
u
b
-
d
is
tr
ict's
s
ilh
o
u
ette
in
d
ex
is
d
is
p
lay
ed
.
T
h
e
v
al
u
e
s
h
o
ws
h
o
w
th
e
cr
ea
te
d
g
r
o
u
p
in
g
s
an
d
s
u
b
-
d
is
tr
icts
ar
e
in
ter
p
r
eted
.
T
h
e
g
r
i
d
is
s
ep
ar
ate
d
f
r
o
m
o
th
er
g
r
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s
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ce
d
b
y
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ex
ce
llen
t
s
ilh
o
u
ette
co
ef
f
icien
t
v
alu
e
n
ea
r
+1
.
T
h
e
g
r
i
d
is
at
o
r
r
ea
s
o
n
a
b
ly
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
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I
n
t J E
lec
&
C
o
m
p
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g
,
Vo
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15
,
No
.
1
,
Feb
r
u
ar
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20
25
:
46
-
55
52
n
ea
r
th
e
d
ec
is
io
n
b
o
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t
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r
id
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r
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is
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L
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s
s
a
y
th
at
th
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v
alu
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alm
o
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t
+1
.
A
g
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h
o
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ld
b
e
in
a
s
ep
ar
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m
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l,
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g
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g
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i
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.
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s
h
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Fig
u
r
e
4
,
th
e
s
ilh
o
u
ette
co
ef
f
icien
t
h
as
a
m
ea
n
v
alu
e
o
f
0
.
7
.
T
a
b
le
2
in
d
icate
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th
at
th
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s
ilh
o
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ette
v
alu
e
is
h
ig
h
er
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an
0
.
7
,
in
d
icatin
g
a
s
o
lid
s
tr
u
ctu
r
e
d
ev
elo
p
e
d
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etwe
en
t
h
e
item
s
.
Fig
u
r
e
3
.
T
h
e
o
p
tim
al
s
ilh
o
u
ette
in
d
ex
d
e
r
iv
ed
u
s
in
g
clu
s
ter
v
alid
ity
p
r
o
ce
d
u
r
es
T
ab
le
6
.
T
o
tal
n
u
m
b
er
o
f
p
ar
ti
cip
an
ts
in
ea
ch
clu
s
ter
k
t
h
c
l
u
st
e
r
N
u
mb
e
r
o
f
m
e
m
b
e
r
s
1
1
3
6
2
4
3
9
4
12
Fig
u
r
e
4
.
Sil
h
o
u
ette
v
alu
e
o
f
o
p
tim
u
m
clu
s
ter
3
.
3
.
Clus
t
er
ing
re
s
ult
v
is
ua
li
za
t
io
n
T
o
f
ac
ilit
ate
ch
ar
ac
ter
is
tic
d
eter
m
in
atio
n
f
r
o
m
ea
ch
ar
ea
,
t
h
e
d
is
tr
ib
u
tio
n
an
d
p
o
s
itio
n
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g
o
f
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ch
s
u
b
d
is
tr
ict's
ar
ea
in
s
id
e
ea
ch
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s
ter
ar
e
th
en
d
is
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lay
ed
b
y
p
lo
ttin
g
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d
m
a
p
p
in
g
th
e
clu
s
ter
in
g
f
in
d
in
g
s
.
Fig
u
r
e
5
d
is
p
lay
s
th
e
ar
ea
'
s
m
ap
p
in
g
r
esu
lts
.
Geo
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r
ap
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in
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cl
u
s
ter
s
2
a
n
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r
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o
m
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at
cl
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e
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I
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&
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min
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io
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y
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ch
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…
(
Gin
a
s
A
l
via
n
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ih
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53
to
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eth
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.
Ho
wev
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,
clu
s
ter
4
i
s
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p
lit
b
etwe
en
th
e
p
r
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v
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ce
'
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west
an
d
s
o
u
th
.
I
n
f
u
tu
r
e
r
ese
ar
ch
,
t
h
is
m
ap
p
i
n
g
ca
n
b
e
th
e
b
asis
f
o
r
d
eter
m
i
n
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th
e
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u
m
l
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a
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m
ass
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o
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lan
t
t
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e
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b
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it
with
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r
a
p
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ical
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n
d
itio
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s
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d
lan
d
u
s
e
m
ap
s
as th
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ad
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itio
n
al
clu
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ter
in
g
v
a
r
iab
les.
Fig
u
r
e
5
.
Ma
p
p
in
g
r
esu
lt o
f
4
clu
s
ter
s
3
.
4
.
Reg
i
o
na
l
cha
ra
ct
er
iza
t
i
o
n
a
na
ly
s
is
T
h
e
r
eg
i
o
n
al
c
h
ar
ac
ter
izatio
n
is
d
eter
m
in
e
d
b
y
g
r
o
u
p
in
g
all
ar
ea
s
u
s
in
g
d
escr
ip
tiv
e
s
tatis
tica
l
tech
n
iq
u
es
f
o
r
ea
ch
cl
u
s
ter
.
C
o
r
r
elatio
n
an
al
y
s
es
ar
e
d
e
v
e
lo
p
ed
u
s
in
g
SP
SS
s
o
f
twar
e.
T
ab
le
7
s
h
o
ws
th
at
clu
s
ter
1
h
as
a
g
o
o
d
b
io
m
ass
p
o
ten
tial
f
o
r
p
alm
o
il
an
d
r
ice
with
a
m
o
d
er
ate
lin
ea
r
r
elatio
n
s
h
ip
.
I
n
clu
s
ter
2
,
th
e
b
io
m
ass
p
o
ten
tial
is
h
ig
h
e
s
t
f
o
r
p
alm
o
il,
co
c
o
n
u
t,
a
r
ec
a
n
u
t,
an
d
r
ice,
with
a
s
tr
o
n
g
lin
ea
r
r
elatio
n
s
h
ip
,
an
d
co
c
o
a,
with
a
m
o
d
er
ate
l
in
ea
r
r
elatio
n
s
h
ip
.
I
n
clu
s
ter
3
,
th
e
b
io
m
ass
p
o
ten
tial
is
h
ig
h
est
f
o
r
p
alm
o
il,
co
co
n
u
t,
r
u
b
b
er
,
a
n
d
c
o
co
a,
with
a
m
o
d
er
ate
lin
ea
r
r
elatio
n
s
h
ip
,
an
d
r
ice
h
as
a
s
tr
o
n
g
li
n
ea
r
r
elatio
n
s
h
ip
.
I
n
clu
s
ter
4
,
th
e
m
o
s
t
b
io
m
ass
p
o
ten
tial
is
co
f
f
ee
a
n
d
r
ice
wit
h
a
m
o
d
e
r
ate
lin
ea
r
r
elatio
n
s
h
ip
.
W
e
ca
n
clea
r
ly
co
n
clu
d
e
t
h
at
all
o
f
th
e
clu
s
ter
h
as r
ice
as a
p
o
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tial c
o
m
m
o
d
ity
.
Fro
m
th
e
an
aly
s
is
r
esu
lts
,
b
io
m
ass
co
n
v
er
s
io
n
tech
n
o
lo
g
y
s
elec
tio
n
ca
n
b
e
ca
r
r
ied
o
u
t
m
o
r
e
ef
f
ec
tiv
ely
b
ased
o
n
th
e
ca
lo
r
if
ic
v
alu
e
o
f
th
e
co
m
m
o
d
ities
in
th
e
clu
s
ter
.
C
lu
s
ter
s
th
at
h
av
e
b
io
m
ass
with
r
elativ
ely
s
m
all
ca
lo
r
if
ic
v
alu
es
m
u
s
t
u
s
e
co
n
v
er
s
io
n
tech
n
o
lo
g
y
with
h
ig
h
er
e
f
f
icien
cy
v
alu
es.
I
n
ad
d
itio
n
,
p
r
o
d
u
ctio
n
ca
p
ac
ity
ca
n
also
b
e
a
co
n
s
tr
ain
t.
I
n
ci
n
er
atio
n
te
ch
n
o
lo
g
y
ca
n
b
e
im
p
lem
en
ted
f
o
r
b
i
o
m
ass
p
o
wer
p
lan
ts
with
lar
g
e
ca
p
ac
ity
,
wh
ile
g
asifica
tio
n
tech
n
o
lo
g
y
ca
n
b
e
im
p
lem
en
te
d
f
o
r
b
io
m
as
s
p
o
wer
p
lan
ts
with
s
m
all
ca
p
ac
ity
[
2
9
]
,
[
3
0
]
.
Fr
o
m
th
e
m
ap
p
in
g
r
esu
lt,
we
ca
n
co
n
clu
d
e
th
at
in
th
is
p
r
o
v
in
ce
m
o
s
t
ar
ea
s
h
av
e
th
e
s
am
e
ch
ar
ac
ter
is
tics
,
s
o
th
e
s
am
e
ty
p
e
o
f
tech
n
o
lo
g
y
ca
n
b
e
ap
p
lied
as we
ll.
As
a
r
esu
lt,
ar
ea
clu
s
ter
izatio
n
ca
n
b
e
ap
p
lied
to
m
ap
t
h
e
b
io
m
ass
p
o
te
n
tial
in
a
p
r
o
v
in
ce
b
y
clu
s
ter
in
g
ea
ch
s
u
b
-
d
is
tr
ict
b
ased
o
n
th
e
b
io
m
ass
p
o
ten
tial
o
wn
ed
an
d
o
th
er
v
a
r
iab
les.
T
h
e
clu
s
ter
r
esu
lts
ar
e
th
en
an
aly
ze
d
f
o
r
ca
lo
r
if
ic
v
alu
e
an
d
ca
p
ac
it
y
s
o
th
at
th
e
ap
p
r
o
p
r
iate
co
n
v
er
s
io
n
t
ec
h
n
o
lo
g
y
ca
n
b
e
d
eter
m
in
ed
.
T
h
is
will
r
esu
lt
i
n
m
o
r
e
ef
f
ec
tiv
e
b
io
m
ass
p
o
wer
p
lan
t
p
lan
n
in
g
in
ter
m
s
o
f
en
er
g
y
co
n
v
er
s
io
n
an
d
also
f
aster
tech
n
o
lo
g
y
d
e
ter
m
in
atio
n
b
ec
au
s
e
th
er
e
is
n
o
n
ee
d
f
o
r
r
ep
ea
te
d
an
aly
s
e
s
f
o
r
s
ev
er
al
ar
ea
s
wh
en
s
ev
er
al
b
io
m
ass
p
o
wer
p
lan
ts
will
b
e
b
u
ilt.
T
o
d
eter
m
in
e
th
e
o
p
tim
al
b
io
m
ass
p
o
wer
p
lan
t
lo
ca
tio
n
p
o
in
t,
s
u
b
clu
s
ter
in
g
ca
n
b
e
ca
r
r
ied
o
u
t
in
a
n
ar
ea
with
d
if
f
er
en
t
v
ar
iab
le
co
n
s
tr
ain
t
s
,
f
o
r
ex
am
p
le,
th
e
ch
ea
p
est co
s
t o
f
tr
an
s
p
o
r
tin
g
b
io
m
ass
to
th
e
p
lan
t o
r
lo
wer
el
ec
tr
ical
p
o
wer
lo
s
s
es.
T
ab
le
7
.
C
o
r
r
elatio
n
co
ef
f
icien
ts
b
etwe
en
th
e
wid
th
o
f
th
e
p
lan
tatio
n
an
d
t
h
e
to
tal
ar
ea
o
f
ea
ch
clu
s
ter
C
l
u
st
e
r
N
u
m
b
e
r
C
o
r
r
e
l
a
t
i
o
n
b
e
t
w
e
e
n
t
h
e
w
i
d
t
h
o
f
t
h
e
p
l
a
n
t
a
t
i
o
n
a
n
d
t
h
e
t
o
t
a
l
a
r
e
a
P
a
l
m O
i
l
C
o
c
o
n
u
t
R
u
b
b
e
r
C
o
f
f
e
e
C
o
c
o
a
A
r
e
c
a
N
u
r
t
S
a
g
o
R
i
c
e
1
0
.
3
8
3
0
.
2
7
8
-
0
.
0
1
4
0
.
0
2
0
.
0
2
0
.
1
4
6
0
.
1
3
0
.
3
1
1
2
0
.
7
4
7
0
.
0
5
7
0
0
.
6
2
3
0
.
6
2
3
0
.
7
3
3
0
0
.
7
3
7
3
0
.
5
1
4
0
.
5
9
9
0
.
2
6
4
0
.
3
0
3
0
.
3
0
3
0
0
0
.
7
8
1
4
-
0
.
3
5
2
-
0
.
3
2
2
0
.
4
0
.
1
1
1
0
.
1
1
1
0
0
0
.
4
4
8
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
1
,
Feb
r
u
ar
y
20
25
:
46
-
55
54
4.
CO
NCLU
SI
O
N
Fro
m
th
e
r
esear
ch
,
we
ca
n
co
n
clu
d
e
th
at
ad
ap
ti
v
e
clu
s
ter
in
g
ca
n
b
e
u
s
ed
to
ar
r
an
g
e
t
h
e
s
u
b
-
d
is
tr
icts
in
to
clu
s
ter
s
th
at
co
n
tain
clu
s
ter
m
em
b
er
s
with
s
im
ilar
p
r
o
f
i
les.
Fro
m
th
e
ch
ar
ac
ter
is
tics
o
f
ea
ch
clu
s
ter
,
we
ca
n
s
elec
t
ap
p
r
o
p
r
iate
b
io
m
a
s
s
co
n
v
er
s
io
n
tech
n
o
lo
g
y
f
o
ll
o
win
g
th
e
ty
p
e
o
f
b
io
m
ass
p
o
ten
tial
to
ac
h
iev
e
o
p
tim
al
p
o
we
r
g
e
n
er
atio
n
o
u
t
p
u
t.
Ar
ea
clu
s
ter
izatio
n
m
eth
o
d
s
an
d
Sil
h
o
u
ette
v
alid
atio
n
will
ac
co
m
m
o
d
ate
th
e
b
est
m
a
p
p
in
g
o
f
b
io
m
ass
p
o
ten
tial.
Fo
r
ea
ch
clu
s
ter
,
th
e
r
esu
lts
o
f
th
e
clu
s
ter
in
g
p
r
o
ce
s
s
wer
e
t
h
u
s
ex
am
in
ed
u
s
in
g
co
r
r
elatio
n
an
aly
s
is
to
d
eter
m
in
e
its
ar
ea
ch
ar
ac
ter
is
tics
.
T
h
e
co
r
r
elatio
n
co
ef
f
icien
t
b
etwe
en
th
e
wid
th
o
f
th
e
p
lan
tatio
n
an
d
th
e
to
tal
ar
ea
ca
n
an
aly
ze
t
h
e
s
ig
n
if
ican
t
b
io
m
ass
p
o
ten
ti
al
in
a
clu
s
ter
.
T
h
e
s
am
e
p
r
o
ce
d
u
r
e
ca
n
b
e
im
p
le
m
en
ted
in
o
th
er
ar
ea
s
.
Fo
r
f
u
tu
r
e
r
esear
ch
,
co
n
v
er
s
io
n
tech
n
o
lo
g
y
d
eter
m
in
atio
n
ca
n
b
e
m
ad
e
b
ased
o
n
th
e
r
an
g
e
o
f
ca
lo
r
if
ic
v
alu
es
o
f
th
e
co
m
m
o
d
ity
in
ea
ch
clu
s
ter
.
Su
b
-
clu
s
ter
in
g
ca
n
also
b
e
u
s
ed
to
d
eter
m
i
n
e
th
e
o
p
tim
al
p
o
in
t
o
f
b
io
m
ass
p
o
wer
p
lan
ts
with
d
if
f
er
en
t
co
n
s
tr
ain
t
v
ar
iab
les,
s
u
ch
as
g
eo
g
r
a
p
h
ical
lan
d
m
a
r
k
s
an
d
lan
d
u
s
e.
RE
F
E
R
E
NC
E
S
[
1
]
G
.
A
l
v
i
a
n
i
n
g
si
h
a
n
d
I
.
G
a
r
n
i
w
a
,
“
A
d
e
s
i
g
n
o
f
p
a
l
m
o
i
l
a
n
d
d
i
e
s
e
l
o
i
l
f
u
e
l
mi
x
t
u
r
e
h
e
a
t
e
r
sy
s
t
e
m
f
o
r
sma
l
l
s
c
a
l
e
d
i
e
se
l
p
o
w
e
r
p
l
a
n
t
,
”
i
n
2
0
1
7
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
H
i
g
h
V
o
l
t
a
g
e
En
g
i
n
e
e
r
i
n
g
a
n
d
Po
w
e
r
S
y
st
e
m
s
(
I
C
H
VEP
S
)
,
O
c
t
.
2
0
1
7
,
p
p
.
1
5
6
–
1
6
4
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
H
V
EPS
.
2
0
1
7
.
8
2
2
5
9
3
4
.
[
2
]
G
.
A
l
v
i
a
n
i
n
g
s
i
h
,
V
.
A
n
t
o
n
o
,
a
n
d
I
.
G
a
r
n
i
w
a
,
“
F
i
n
a
n
c
i
a
l
a
n
d
t
e
c
h
n
i
c
a
l
f
o
r
e
c
a
s
t
a
n
a
l
y
si
s
o
f
a
h
y
b
r
i
d
b
i
o
m
a
ss
-
d
i
e
se
l
p
o
w
e
r
p
l
a
n
t
:
C
a
se
s
t
u
d
y
i
n
T
i
n
g
g
i
I
sl
a
n
d
,
S
o
u
t
h
B
a
n
g
k
a
,
”
i
n
2
0
2
1
3
rd
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
H
i
g
h
V
o
l
t
a
g
e
E
n
g
i
n
e
e
ri
n
g
a
n
d
P
o
w
e
r
S
y
s
t
e
m
s,
I
C
H
VE
PS
2
0
2
1
,
O
c
t
.
2
0
2
1
,
v
o
l
.
1
1
,
p
p
.
3
0
5
–
3
0
8
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
H
V
EPS
5
3
1
7
8
.
2
0
2
1
.
9
6
0
1
1
0
2
.
[
3
]
I
.
G
a
r
n
i
w
a
,
G
.
A
l
v
i
a
n
i
n
g
si
h
,
a
n
d
V
.
A
n
t
o
n
o
,
“
W
a
st
e
t
o
e
n
e
r
g
y
i
m
p
l
e
me
n
t
a
t
i
o
n
u
s
i
n
g
g
a
si
f
i
c
a
t
i
o
n
t
e
c
h
n
o
l
o
g
y
i
n
Ti
n
g
g
i
I
sl
a
n
d
,
”
E3
S
W
e
b
o
f
C
o
n
f
e
re
n
c
e
s
,
v
o
l
.
2
1
1
,
2
0
2
0
,
d
o
i
:
1
0
.
1
0
5
1
/
e
3
sc
o
n
f
/
2
0
2
0
2
1
1
0
3
0
0
5
.
[
4
]
I
.
D
i
n
c
e
r
,
“
R
e
n
e
w
a
b
l
e
e
n
e
r
g
y
a
n
d
s
u
st
a
i
n
a
b
l
e
d
e
v
e
l
o
p
me
n
t
:
a
c
r
u
c
i
a
l
r
e
v
i
e
w
,
”
Re
n
e
w
a
b
l
e
&
s
u
st
a
i
n
a
b
l
e
e
n
e
r
g
y
re
v
i
e
w
s
,
v
o
l
.
4
,
n
o
.
2
,
p
p
.
1
5
7
–
1
7
5
,
Ju
n
.
2
0
0
0
,
d
o
i
:
1
0
.
1
0
1
6
/
S
1
3
6
4
-
0
3
2
1
(
9
9
)
0
0
0
1
1
-
8.
[
5
]
B
.
C
.
H
.
S
i
m
a
n
g
u
n
so
n
g
e
t
a
l
.
,
“
P
o
t
e
n
t
i
a
l
f
o
r
e
st
b
i
o
mass
r
e
s
o
u
r
c
e
a
s
f
e
e
d
s
t
o
c
k
f
o
r
b
i
o
e
n
e
r
g
y
a
n
d
i
t
s
e
c
o
n
o
mi
c
v
a
l
u
e
i
n
I
n
d
o
n
e
s
i
a
,
”
Fo
res
t
Po
l
i
c
y
a
n
d
Ec
o
n
o
m
i
c
s
,
v
o
l
.
8
1
,
p
p
.
1
0
–
1
7
,
A
u
g
.
2
0
1
7
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
f
o
r
p
o
l
.
2
0
1
7
.
0
3
.
0
2
2
.
[
6
]
L.
C
o
n
r
a
d
a
n
d
I
.
P
r
a
set
y
a
n
i
n
g
,
O
v
e
r
v
i
e
w
o
f
t
h
e
w
a
s
t
e
-
to
-
e
n
e
rg
y
p
o
t
e
n
t
i
a
l
f
o
r
g
ri
d
-
c
o
n
n
e
c
t
e
d
e
l
e
c
t
r
i
c
i
t
y
g
e
n
e
ra
t
i
o
n
(
so
l
i
d
b
i
o
m
a
ss
a
n
d
b
i
o
g
a
s)
i
n
I
n
d
o
n
e
s
i
a
.
L
C
O
R
E
-
I
n
d
o
,
2
0
1
4
.
[
7
]
G
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d
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t
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a
rd
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g
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(BEM
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a
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d
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AEM
A
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rti
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Train
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e
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a
n
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r
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in
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rse
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TC),
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re
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ti
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p
ro
jec
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d
o
ff
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d
s
o
lar
P
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d
e
sig
n
.
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h
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is
th
e
a
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r
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d
c
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a
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r
o
f
m
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re
th
a
n
8
0
p
u
b
l
ica
ti
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s
in
in
tern
a
ti
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a
l
jo
u
rn
a
ls
a
n
d
p
r
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d
in
g
s
i
n
p
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we
r
s
y
ste
m
s
a
n
d
e
n
e
rg
y
.
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r
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
n
e
two
rk
re
c
o
n
fig
u
ra
ti
o
n
,
o
p
ti
m
iza
ti
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tec
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S
h
e
c
a
n
b
e
c
o
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tac
ted
a
t
e
m
a
il
:
h
a
sle
n
d
a
@u
t
m
.
m
y
.
J
a
sr
u
l
J
a
m
a
n
i
J
a
m
i
a
n
re
c
e
iv
e
d
a
Ba
c
h
e
lo
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f
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n
g
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rin
g
(B.
En
g
.
(Ho
n
s))
d
e
g
re
e
,
M
a
ste
r
o
f
E
n
g
i
n
e
e
rin
g
(
M
.
En
g
.
),
a
n
d
P
h
.
D
d
e
g
re
e
in
e
l
e
c
tri
c
a
l
(p
o
we
r)
e
n
g
in
e
e
ri
n
g
fro
m
Un
i
v
e
rsiti
Tek
n
o
lo
g
i
M
a
la
y
sia
in
2
0
0
8
,
2
0
1
0
,
a
n
d
2
0
1
3
,
re
sp
e
c
ti
v
e
ly
.
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is
c
u
rre
n
tl
y
t
h
e
D
irec
to
r
o
f
th
e
P
o
we
r
En
g
i
n
e
e
rin
g
Div
isio
n
a
t
th
e
S
c
h
o
o
l
o
f
El
e
c
tr
ica
l
En
g
in
e
e
ri
n
g
,
Un
iv
e
rsiti
Tek
n
o
lo
g
i
M
a
lay
sia
.
He
is
a
c
ti
v
e
ly
i
n
v
o
lv
e
d
in
re
se
a
rc
h
a
s
a
p
rin
c
ip
a
l
in
v
e
stig
a
t
o
r
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n
d
lea
d
e
r
in
c
o
n
su
lt
a
n
c
y
p
ro
jec
ts
wit
h
se
v
e
ra
l
c
o
m
p
a
n
ies
,
s
u
c
h
a
s
P
e
tr
o
n
a
s
a
n
d
Ten
a
g
a
Na
sio
n
a
l
Be
rh
a
d
,
wh
ich
fo
c
u
se
s o
n
re
lay
c
o
o
r
d
in
a
ti
o
n
p
r
o
jec
ts an
d
o
ff
-
g
ri
d
so
lar P
V
d
e
sig
n
.
He
is t
h
e
a
u
t
h
o
r
a
n
d
co
-
a
u
th
o
r
o
f
m
o
re
th
a
n
8
0
p
u
b
l
ica
ti
o
n
s
i
n
in
tern
a
ti
o
n
a
l
j
o
u
r
n
a
ls
a
n
d
p
ro
c
e
e
d
in
g
s
i
n
p
o
we
r
sy
ste
m
s
a
n
d
e
n
e
r
g
y
.
His
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
n
e
two
rk
re
c
o
n
fig
u
ra
ti
o
n
,
o
p
ti
m
iza
ti
o
n
tec
h
n
iq
u
e
s,
a
n
d
re
n
e
wa
b
le en
e
rg
y
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
ja
sru
l@fk
e
.
u
tm.m
y
.
Adri
S
e
n
e
n
re
c
e
iv
e
d
a
b
a
c
h
e
lo
r'
s
d
e
g
re
e
in
e
lec
tri
c
a
l
e
n
g
in
e
e
r
in
g
fro
m
An
d
a
la
s
Un
iv
e
rsity
,
In
d
o
n
e
sia
,
in
2
0
0
4
a
n
d
a
M
a
ste
r'
s
d
e
g
re
e
in
e
lec
tri
c
a
l
p
o
we
r
e
n
g
i
n
e
e
rin
g
fr
o
m
Ba
n
d
u
n
g
In
st
it
u
te
o
f
Tec
h
n
o
l
o
g
y
(IT
B),
I
n
d
o
n
e
sia
,
in
2
0
0
8
.
He
is
a
P
h
D
st
u
d
e
n
t
i
n
th
e
F
a
c
u
lt
y
o
f
El
e
c
tri
c
a
l
En
g
i
n
e
e
rin
g
a
t
Un
iv
e
rsiti
Tek
n
o
l
o
g
i
M
a
lay
sia
.
His
re
se
a
rc
h
in
tere
sts
c
o
n
c
e
rn
lo
a
d
fo
re
c
a
stin
g
,
m
a
n
a
g
e
m
e
n
t
e
n
e
rg
y
,
e
lec
tri
c
a
l
p
lan
n
i
n
g
,
re
n
e
wa
b
le
e
n
e
rg
y
,
a
n
d
p
o
we
r
sy
ste
m
s.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
a
d
r
i
se
n
e
n
@itp
l
n
.
a
c
.
id
.
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