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1.
I
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RO
D
UCT
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N
T
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p
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ev
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an
d
th
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ev
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its
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[
1
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T
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to
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tain
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b
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th
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tr
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[
2
]
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th
is
,
allo
w
th
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t
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cr
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3
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a
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[4
-
6]
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[
7
,
8
]
,
a
n
d
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v
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,
t
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m
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s
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m
s
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f
[
9
,
1
0
]
.
Fu
r
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s
,
s
p
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Su
ch
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d
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to
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[
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1
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ten
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s
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p
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b
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[
1
2
]
.
T
h
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latter
u
s
u
ally
in
clu
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e
g
r
a
d
ien
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b
ased
alg
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r
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m
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r
ee
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g
o
r
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ev
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alg
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,
an
d
n
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r
e
-
in
s
p
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m
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-
h
eu
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is
tics
[
1
3
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.
A
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ased
alg
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ith
m
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m
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s
[
1
3
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;
th
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Qu
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New
to
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m
eth
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s
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r
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I
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18
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6
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18
3012
co
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v
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r
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at
s
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f
r
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m
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.
Oth
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g
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alg
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r
ith
m
s
(
GA)
im
p
ly
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s
b
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itab
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s
o
lu
tio
n
s
to
a
g
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p
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[
1
3
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.
I
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ee
d
in
g
,
an
d
m
u
tatio
n
to
estab
lis
h
h
o
w
s
u
r
v
iv
al
a
n
d
s
o
lu
tio
n
p
r
o
p
ag
atio
n
wo
u
ld
b
e
af
f
ec
ted
[
1
1
]
.
C
r
o
p
s
’
o
u
tco
m
e
is
m
ea
s
u
r
ed
r
eg
ar
d
in
g
its
p
er
f
o
r
m
an
ce
an
d
co
n
s
id
er
in
g
th
e
f
a
cto
r
s
(
clim
a
tic,
b
io
tic,
an
d
ed
a
p
h
ic)
th
at
c
o
u
ld
af
f
ec
t th
em
;
s
u
ch
f
ac
to
r
s
an
d
its
co
n
s
titu
en
ts
im
p
ac
t
o
n
th
e
cr
o
p
s
i
s
n
ev
er
is
o
lated
,
o
n
th
e
co
n
tr
ar
y
,
it
is
in
ter
d
e
p
en
d
e
n
t
[
1
5
]
.
Acc
o
r
d
in
g
to
Sy
n
g
en
t
a,
s
u
b
-
f
ac
to
r
s
as
s
o
lar
r
ad
iatio
n
(
g
r
o
win
g
)
;
r
ain
f
all
v
o
lu
m
e
a
n
d
s
o
il
(
lim
itin
g
)
;
a
n
d
p
lag
u
es
an
d
illn
ess
es
(
r
ed
u
ctio
n
)
,
d
ir
ec
tly
af
f
ec
t
th
e
c
r
o
p
s
’
p
er
f
o
r
m
a
n
ce
.
Fu
r
th
er
m
o
r
e
,
b
io
m
ass
is
s
y
n
th
esized
v
ia
b
io
tic
o
r
g
an
ic
co
m
p
o
n
en
ts
in
wh
ic
h
wate
r
in
te
r
ce
d
e
as
th
e
v
eh
icle
f
o
r
ch
em
ical
r
ea
ctio
n
s
an
d
s
o
lar
r
a
d
iatio
n
s
u
p
p
o
r
ts
th
e
en
er
g
etic
n
ee
d
s
o
f
t
h
e
cr
o
p
[
1
6
]
.
T
h
er
ef
o
r
e,
b
io
m
ass
,
r
ain
f
all
v
o
lu
m
e,
s
o
lar
r
ad
iatio
n
,
an
d
in
-
f
ield
wate
r
e
x
tr
ac
tio
n
s
,
will
b
e
th
e
s
u
b
-
f
ac
to
r
s
estab
lis
h
ed
to
d
ev
el
o
p
th
e
p
r
ed
ictio
n
m
o
d
el
f
o
r
w
h
ea
t c
r
o
p
in
t
h
is
r
esear
ch
.
T
h
is
r
esear
ch
p
r
esen
ts
an
ev
alu
atio
n
o
f
th
e
p
r
ed
ictiv
e
m
o
d
el
p
er
f
o
r
m
an
ce
th
r
o
u
g
h
co
m
p
a
r
is
o
n
of
two
co
n
f
ig
u
r
atio
n
s
b
ased
o
n
th
e
f
u
zz
y
s
et
th
eo
r
y
f
o
r
t
h
e
f
o
r
ec
asti
n
g
o
f
a
wh
ea
t
cr
op
y
ield
in
g
:
g
e
n
er
ic
Qu
asi
-
New
to
n
g
r
ad
i
en
t
alg
o
r
ith
m
(
tr
a
d
itio
n
al
o
p
tim
izatio
n
)
an
d
GA
(
h
eu
r
is
tic
m
eth
o
d
)
.
T
h
is
d
o
c
u
m
en
t
will
d
e
f
in
e
th
e
r
esear
ch
m
eth
o
d
;
its
co
n
f
ig
u
r
atio
n
s
an
d
th
e
o
p
tim
iza
tio
n
tech
n
iq
u
es
u
s
ed
;
an
d
will
p
r
esen
t
a
b
r
ief
d
escr
ip
tio
n
r
eg
a
r
d
i
n
g
th
e
APSi
m
d
ata
-
s
et
u
s
ed
an
d
t
h
e
d
ata
e
x
tr
ac
ted
f
r
o
m
[
1
7
]
.
2.
RE
L
AT
E
D
R
E
SE
ARCH
Mo
d
if
ied
GAs
ca
n
s
o
lv
e
m
u
l
ti
tar
g
et
is
s
u
es
wh
er
e
s
to
ch
asti
c
o
p
tim
izatio
n
is
a
m
u
s
t
an
d
ca
n
h
elp
cu
ltiv
ato
r
s
to
m
ak
e
b
etter
d
ec
is
io
n
s
r
eg
ar
d
in
g
th
e
c
o
s
t/u
tili
ty
r
atio
o
n
a
g
r
icu
ltu
r
al
o
p
er
ati
o
n
s
[
1
8
]
;
o
n
e
o
f
its
u
s
es
ca
n
b
e
s
ee
n
in
th
e
esti
m
atio
n
o
n
th
e
c
h
an
g
e
tim
es
f
o
r
m
ed
iu
m
s
ize
m
ac
ad
am
ia
n
u
t
cr
o
p
s
.
As
p
ar
t
o
f
th
e
m
o
d
e
r
n
a
g
r
icu
ltu
r
al
p
r
ac
ti
ce
s
,
g
r
ee
n
h
o
u
s
e
cr
o
p
p
in
g
r
e
q
u
ir
es
ac
cu
r
ate
m
o
d
els
f
o
r
p
lan
t g
r
o
win
g
(
an
d
o
th
e
r
p
ar
am
eter
s
)
u
n
d
er
a
s
er
ies
o
f
c
lim
atic
f
ac
to
r
s
.
T
o
s
o
lv
e
s
u
ch
p
r
o
b
lem
r
esear
ch
was
ca
r
r
ied
o
u
t
th
r
o
u
g
h
a
d
o
u
b
l
e
GA
in
wh
ich
th
e
p
r
im
ar
y
al
g
o
r
ith
m
p
a
r
am
eter
ize
th
e
m
o
d
el,
wh
ile
th
e
s
ec
o
n
d
ar
y
o
n
e
d
ef
in
es
th
e
in
itial
alg
o
r
ith
m
ic
p
a
r
am
eter
s
[
1
9
]
.
An
o
p
tim
i
za
tio
n
m
eth
o
d
,
b
ased
o
n
an
AC
O
an
d
o
n
an
ad
v
an
ce
d
Pro
ce
s
s
-
f
o
cu
s
ed
cr
o
p
p
i
n
g
m
o
d
el,
an
d
test
ed
o
n
a
co
r
n
cr
o
p
in
C
o
lo
r
ad
o
(
USA)
,
was
ca
r
r
ied
o
u
t
to
r
ed
u
ce
th
e
wate
r
an
d
f
er
tili
ze
r
u
s
e
to
its
m
in
im
u
m
tak
in
g
in
to
ac
co
u
n
t
th
e
b
io
s
y
s
tem
’
s
r
ef
er
en
ce
[
2
0
]
.
GAs
im
p
lem
en
tatio
n
o
n
r
ice
cr
o
p
s
wo
u
l
d
d
er
iv
e
o
n
m
o
d
els
to
im
p
r
o
v
e
b
o
th
,
p
r
o
d
u
ctiv
ity
an
d
q
u
ality
,
wh
ile
o
p
tim
izin
g
its
y
ield
in
g
.
On
th
e
m
o
d
el
p
r
o
p
o
s
ed
f
o
r
r
is
e
cu
ltiv
atio
n
1
6
p
ar
am
eter
s
ar
e
m
in
d
ed
to
alter
th
e
p
e
r
f
o
r
m
an
ce
o
f
th
e
ce
r
ea
l
d
r
o
p
s
in
T
h
ail
an
d
,
o
n
th
is
ex
a
m
p
le
r
is
k
m
an
ag
em
en
t
is
in
clu
d
e
d
as
an
o
u
tco
m
e
an
d
th
r
o
u
g
h
o
u
t
iter
atio
n
s
o
n
th
e
r
is
k
lev
el
o
v
er
th
e
r
ice
cr
o
p
s
th
e
less
er
r
is
k
s
o
lu
tio
n
was a
ttain
ed
[
2
1
]
.
Sto
ch
asti
c
alg
o
r
ith
m
s
ca
n
b
e
co
m
b
in
ed
to
g
en
er
ate
h
y
b
r
id
m
eta
-
h
eu
r
is
tics
.
I
n
th
is
ca
s
e,
t
h
e
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
PSO
)
,
im
p
er
ialis
t
co
m
p
etitiv
e
alg
o
r
ith
m
(
I
C
A
)
,
an
d
s
u
p
p
o
r
t
v
ec
to
r
r
eg
r
ess
io
n
(
SVR
)
wer
e
co
m
b
in
ed
t
o
p
r
ed
ict
th
e
p
er
f
o
r
m
an
ce
o
f
a
p
r
ico
t
cr
o
p
s
in
Ab
ar
k
u
h
Yaz
d
(
I
r
a
n
)
:
6
1
v
ar
iab
l
es
wer
e
co
n
s
id
er
ed
,
1
8
o
f
th
o
s
e
wer
e
m
o
r
e
in
f
l
u
en
t
ial
o
n
th
e
cr
o
p
s
’
p
er
f
o
r
m
an
ce
ac
co
r
d
in
g
to
th
e
u
s
e
o
f
th
e
h
y
b
r
id
alg
o
r
ith
m
[
2
2
]
.
An
o
th
er
m
an
n
e
r
to
ac
cu
r
ately
esti
m
ate
th
e
p
er
f
o
r
m
a
n
ce
o
f
a
cr
o
p
is
u
s
in
g
d
ata
an
d
i
n
d
ex
es
f
r
o
m
cr
o
p
-
g
r
o
win
g
s
im
u
latio
n
to
o
ls
.
Fo
r
in
s
tan
ce
,
th
is
r
esear
ch
ass
u
m
ed
b
io
m
ass
an
d
d
o
s
el
co
v
er
s
c
o
m
in
g
f
r
o
m
th
e
v
eg
etatio
n
in
d
ex
es
o
n
t
h
e
aq
u
a
cr
o
p
s
im
u
latio
n
m
o
d
el
(
FAO)
,
th
r
o
u
g
h
a
PS
O,
to
o
b
t
ain
m
o
r
e
ac
c
u
r
ate
esti
m
atio
n
s
f
o
r
th
o
s
e
f
ac
to
r
s
o
n
c
o
r
n
c
r
o
p
s
.
T
h
e
o
u
tc
o
m
e
was
v
alid
ate
d
t
h
r
o
u
g
h
a
n
r
o
o
t
-
m
ea
n
-
s
q
u
ar
e
er
r
o
r
(
R
MSE
)
an
d
co
m
p
ar
ed
to
o
th
e
r
v
e
g
etatio
n
i
n
d
ex
es
[
2
3
]
.
3.
RE
S
E
ARCH
M
E
T
H
O
D
T
h
e
ap
p
licatio
n
o
f
an
ex
p
e
r
im
en
tal
m
eth
o
d
all
o
ws
th
e
ad
ap
tatio
n
o
f
t
h
e
en
v
ir
o
n
m
e
n
t
to
o
b
tain
a
n
ex
p
ec
ted
r
esu
lt,
lo
o
k
i
n
g
f
o
r
th
e
ch
ar
ac
ter
is
tics
an
d
p
r
o
p
er
t
ies
r
elev
an
t
in
th
e
ex
p
er
im
en
t
[
2
4
]
.
I
t
f
o
cu
s
es
o
n
th
e
an
aly
s
is
o
f
th
e
s
et
o
f
r
ec
o
r
d
s
th
at
d
escr
ib
e
cr
o
p
b
eh
av
io
r
i
n
ter
m
s
o
f
cr
itical
v
ar
iab
les
an
d
y
ield
.
T
h
is
s
ec
tio
n
d
escr
ib
es
th
e
f
lo
w
o
f
ac
tiv
ities
ca
r
r
ied
o
u
t
t
o
o
b
tai
n
th
e
o
p
tim
al
v
alu
e
f
o
r
p
er
f
o
r
m
an
c
e.
E
ac
h
s
u
b
s
ec
tio
n
r
ep
r
esen
ts
a
c
o
n
f
i
g
u
r
atio
n
as
f
o
llo
ws:
th
e
f
ir
s
t
c
o
r
r
esp
o
n
d
s
to
th
e
co
n
f
ig
u
r
ati
o
n
o
f
th
e
f
u
zz
y
s
y
s
tem
s
an
d
th
e
s
ec
o
n
d
to
th
e
im
p
lem
en
tat
io
n
o
f
o
p
tim
izatio
n
tech
n
iq
u
e
s
.
T
h
is
r
esear
ch
u
s
ed
6
8
0
d
aily
co
m
p
iled
d
atasets
r
eg
ar
d
in
g
wh
ea
t c
r
o
p
s
f
r
o
m
th
e
APSi
m
f
r
am
ewo
r
k
:
3
.
1
.
F
uzzy
s
et
co
nfig
ura
t
io
n
I
n
MA
T
L
AB
,
two
co
n
f
ig
u
r
ati
o
n
s
wer
e
s
et;
b
o
th
with
th
e
a
b
o
v
e
m
en
tio
n
ed
f
o
u
r
in
p
u
t
f
a
cto
r
s
an
d
a
s
in
g
le
o
u
tco
m
e
(
cr
o
p
p
er
f
o
r
m
an
ce
)
r
esp
o
n
d
in
g
to
th
e
in
te
r
a
ctio
n
o
f
th
e
in
p
u
t
d
ata.
T
h
e
f
i
r
s
t
co
n
f
ig
u
r
atio
n
is
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
P
r
ed
ictio
n
s
o
n
w
h
ea
t c
r
o
p
yiel
d
in
g
th
r
o
u
g
h
fu
z
z
y
s
et
th
eo
r
y
a
n
d
… (
J
u
lio
B
a
r
ó
n
V
ela
n
d
ia
)
3013
b
ased
o
n
Ma
m
d
an
i
m
o
d
el
with
a
s
im
p
le
s
tr
u
ct
u
r
e
o
f
o
p
er
ato
r
s
“m
in
-
m
ax
”;
1
6
f
u
zz
y
i
n
f
er
en
ce
r
u
les
ar
e
ad
ju
s
ted
;
an
d
ea
ch
in
p
u
t
an
d
o
u
tp
u
t
ar
e
ass
ig
n
ed
with
3
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e
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im
f
f
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:
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m
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ig
h
.
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h
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s
ec
o
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ig
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u
s
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th
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T
ak
ag
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-
Su
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en
o
m
o
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el,
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s
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tr
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eg
ar
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m
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d
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Fig
u
r
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ig
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Fig
u
r
e
1
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Def
in
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n
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ig
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r
atio
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o
f
f
u
zz
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tem
s
3
.
2
.
O
pti
m
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io
n t
e
chniq
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s
T
w
o
o
p
t
i
m
i
z
a
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o
n
a
l
g
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a
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d
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a
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h
c
o
n
f
i
g
u
r
a
t
i
o
n
d
e
f
i
n
e
d
:
t
h
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f
i
r
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t
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n
e
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d
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t
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m
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e
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;
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e
r
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r
(
MS
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As
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t
;
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e
n
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a
l
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n
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e
d
i
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d
d
a
t
a
.
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h
i
s
a
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p
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i
g
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2
s
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m
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r
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th
m
s
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Fig
u
r
e
2
.
Gen
e
r
al
o
p
e
r
atio
n
o
f
o
p
tim
izatio
n
alg
o
r
ith
m
s
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Fig
u
r
e
3
.
Pro
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s
s
f
lo
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r
f
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zy
s
y
s
tem
s
u
s
in
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o
p
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o
r
ith
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4.
O
UT
CO
M
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S AN
D
DIS
CUS
SI
O
N
T
h
is
s
ec
tio
n
p
r
esen
ts
th
e
r
esu
lt
s
o
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tain
ed
f
r
o
m
th
e
im
p
lem
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n
tatio
n
o
f
th
e
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r
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ed
c
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n
f
ig
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s
f
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th
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f
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ets
an
d
th
eir
r
esp
ec
tiv
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o
p
tim
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n
tech
n
i
q
u
es.
T
ab
les
d
escr
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e
th
e
p
er
f
o
r
m
an
ce
i
n
d
ices
in
ter
m
s
o
f
ac
cu
r
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a
n
d
e
r
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r
.
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th
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n
d
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th
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ig
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r
es
r
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f
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n
g
m
ad
e
b
y
th
e
b
est m
o
d
els.
4
.
1
.
G
ener
ic
Q
ua
s
i
-
New
t
o
n
g
ra
dient
a
lg
o
rit
hm
C
o
n
f
ig
u
r
atio
n
1
: M
am
d
a
n
i sy
s
tem
(
tr
im
f
f
u
n
ctio
n
)
1
6
r
u
les.
C
o
n
f
ig
u
r
atio
n
2
: Su
g
e
n
o
s
y
s
tem
(
g
au
s
s
m
f
f
u
n
ctio
n
)
1
0
r
u
les
.
T
ab
le
1
s
h
o
ws
th
e
p
e
r
f
o
r
m
an
c
e
in
d
ex
r
elate
d
t
o
th
e
two
co
n
f
ig
u
r
atio
n
s
f
o
r
a
g
r
ad
ien
t
-
b
ase
d
m
eth
o
d
:
er
r
o
r
o
n
th
e
f
ir
s
t
co
n
f
i
g
u
r
atio
n
was
0
.
0
0
5
4
3
3
an
d
0
.
0
0
6
3
6
5
o
n
th
e
s
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o
n
d
.
T
h
e
ac
cu
r
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cy
p
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n
tag
e
was
9
9
.
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2
6
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d
9
9
.
9
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0
ac
co
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d
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y
;
as
th
e
f
ir
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t
co
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f
ig
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n
h
as
th
e
b
etter
ac
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r
ac
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an
d
less
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r
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r
is
d
ec
lar
ed
th
e
b
est
p
er
f
o
r
m
an
ce
o
u
tco
m
e
.
Fig
u
r
es
4
an
d
5
s
h
o
w
th
e
M
SE
in
th
e
f
ir
s
t
5
0
d
ataset
f
o
r
b
o
th
co
n
f
i
g
u
r
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s
.
Fig
u
r
es
6
an
d
7
s
h
o
w
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co
m
p
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is
o
n
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etwe
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t
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n
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e
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tim
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d
ata
f
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r
b
o
th
c
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n
f
ig
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r
at
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n
s
in
a
r
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e
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f
5
0
d
atasets
.
T
h
is
wo
u
ld
allo
w
th
e
r
esear
ch
es to
ex
em
p
lify
th
e
b
eh
av
io
r
o
f
th
e
s
er
ies.
T
ab
le
1
.
Per
f
o
r
m
an
ce
in
d
ices
f
o
r
co
n
f
ig
u
r
atio
n
s
ap
p
lied
to
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h
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g
r
ad
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n
t b
ase
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eth
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d
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f
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g
M
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M
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S
TD
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Qu
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to
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Fig
u
r
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5
.
MSE
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esp
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d
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Qu
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Fig
u
r
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6
.
C
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f
r
o
m
th
e
f
ir
s
t c
o
n
f
ig
u
r
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n
f
o
r
th
e
Qu
asi
-
New
to
n
g
r
ad
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n
t te
ch
n
iq
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e
Fig
u
r
e
7
.
C
o
m
p
a
r
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n
o
f
r
ea
l
v
alu
es with
th
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s
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p
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ed
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f
r
o
m
th
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f
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f
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Qu
asi
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ch
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e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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18
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6
,
Dec
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e
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0
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4
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1
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d
a
n
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s
tem
(
tr
im
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Evaluation Warning : The document was created with Spire.PDF for Python.
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lah
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In
ter
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[3
]
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K.
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u
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.
[4
]
F
.
Ja
wa
d
,
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a
l.
,
“
An
a
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.
[5
]
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.
N.
De
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.
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,
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p
.
1
4
7
3
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4
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6
,
2
0
1
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.
[6
]
S
.
B.
Zi
n
n
a
t
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d
D.
M
.
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d
u
ll
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h
,
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)
,
p
p
.
1
7
0
-
1
7
3
,
2
0
1
4
[7
]
A.
Da
n
iel,
P
.
S
h
a
rm
a
,
a
n
d
R.
S
ri
v
a
sta
v
a
,
“
F
u
z
z
y
Ba
se
d
P
re
d
ictio
n
M
o
d
e
l
Us
in
g
Ra
in
fa
ll
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a
ra
m
e
ter
fo
r
No
rth
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d
ia
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a
ize
p
ro
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c
ti
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n
,
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2
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8
5
t
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IEE
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Utt
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r P
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ter
E
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g
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ON)
,
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p
.
1
-
6
,
2
0
1
8
.
[8
]
A.
An
it
h
a
a
n
d
D.
P
.
Ac
h
a
rjy
a
,
“
Cro
p
s
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y
p
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n
in
Ve
ll
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r
e
District
u
sin
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se
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o
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fu
z
z
y
a
p
p
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x
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ti
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sp
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d
n
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two
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k
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,
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l.
3
0
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n
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p
p
.
3
6
3
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-
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6
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0
,
2
0
1
8
.
[9
]
G
.
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ra
b
a
k
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ra
n
,
D.
Va
it
h
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y
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n
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t
h
a
n
,
a
n
d
M
.
G
a
n
e
sa
n
,
“
F
u
z
z
y
d
e
c
isio
n
su
p
p
o
rt
sy
ste
m
f
o
r
imp
r
o
v
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n
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th
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p
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ti
v
it
y
a
n
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e
fficie
n
t
u
se
o
f
f
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rti
li
z
e
rs,”
Co
mp
u
t
.
El
e
c
tro
n
.
A
g
r
ic.
,
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l.
1
5
0
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o
.
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a
rc
h
,
p
p
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1
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.
[1
0
]
I.
C.
Va
len
z
u
e
la,
R
.
G
.
Ba
ld
o
v
in
o
,
A.
A.
Ba
n
d
a
la,
a
n
d
E.
P
.
Da
d
io
s,
“
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ro
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F
u
z
z
y
In
fe
re
n
c
e
S
y
ste
m
(AN
F
IS
),
”
2
0
1
7
In
ter
n
a
ti
o
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a
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Co
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fer
e
n
c
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Co
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u
ter
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d
Ap
p
li
c
a
ti
o
n
s (ICCA
)
,
p
p
.
1
2
9
-
1
3
4
,
2
0
1
7
.
[1
1
]
J.
R.
P
re
z
L
p
e
z
,
“
Co
n
tri
b
u
c
i
n
a
lo
s
m
to
d
o
s
d
e
o
p
t
imiz
a
c
i
n
b
a
sa
d
o
s
e
n
p
r
o
c
e
so
s
n
a
tu
ra
les
y
su
a
p
li
c
a
c
i
n
a
la
m
e
d
id
a
d
e
a
n
te
n
a
s e
n
c
a
m
p
o
p
r
x
imo
,
”
Un
i
v
e
rsid
a
d
d
e
Ca
n
tab
ria,
2
0
0
7
.
[1
2
]
A.
Da
rwish
,
“
Bio
-
i
n
sp
ired
c
o
m
p
u
ti
n
g
:
Al
g
o
rit
h
m
s
re
v
iew
,
d
e
e
p
a
n
a
ly
sis,
a
n
d
th
e
sc
o
p
e
o
f
a
p
p
li
c
a
ti
o
n
s,”
F
u
tu
r.
Co
mp
u
t
.
In
fo
rm
a
t
ics
J
.
,
v
o
l.
3
,
n
o
.
2
,
p
p
.
2
3
1
-
2
4
6
,
2
0
1
8
.
[1
3
]
X.
S
.
Ya
n
g
,
"
In
tr
o
d
u
c
ti
o
n
t
o
a
lg
o
rit
h
m
s
fo
r
d
a
ta
m
in
i
n
g
a
n
d
m
a
c
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rn
in
g
,
"
1
st
e
d
.
L
o
n
d
o
n
,
U
n
i
ted
Kin
g
d
o
m:
El
se
v
ier
In
c
,
2
0
1
9
.
[1
4
]
R
.
H
a
u
s
e
r
,
“
Q
u
a
s
i
-
N
e
w
t
o
n
M
e
t
h
o
d
s
,
”
O
x
f
o
r
d
,
2
0
0
6
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
:
/
/
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w
w
.
n
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m
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.
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l
.
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c
.
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k
/
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/
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4
s
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s
.
p
d
f
.
[1
5
]
J.
G
.
M
a
rín
M
o
ra
les
,
“
F
a
c
to
re
s
q
u
e
a
fe
c
tan
e
l
c
re
c
imi
e
n
to
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las
p
lan
tas
,
”
Co
rp
o
ra
c
ió
n
Co
lo
mb
.
In
v
e
stig
.
A
g
ro
p
e
c
u
.
,
2
0
1
8
,
Ac
c
e
ss
e
d
:
Ap
r.
0
8
,
2
0
2
0
.
[
On
li
n
e
].
A
v
a
il
a
b
le:
h
tt
p
:/
/
h
d
l.
h
a
n
d
le.n
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t/
2
0
.
5
0
0
.
1
2
3
2
4
/2
2
0
3
3
.
[1
6
]
A.
M
a
rtí
n
e
z
Ro
m
e
ro
a
n
d
A.
Le
y
v
a
G
a
lán
,
“
La
b
io
m
a
sa
d
e
lo
s
c
u
lt
iv
o
s
e
n
e
l
a
g
r
o
e
c
o
siste
m
a
.
S
u
s
b
e
n
e
fici
o
s
a
g
ro
e
c
o
l
g
ico
s,”
C
u
lt
iv.
T
ro
p
.
,
v
o
l.
3
5
,
n
o
.
1
,
p
p
.
1
1
-
2
0
,
2
0
1
4
,
[1
7
]
N
.
D
a
l
g
l
i
e
s
h
,
e
t
a
l
.
,
"
E
x
p
a
n
d
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n
g
t
h
e
a
r
e
a
f
o
r
R
a
b
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-
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a
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B
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l
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,
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1
s
t
e
d
.
A
u
s
t
r
a
l
i
a
:
A
C
I
A
R
,
2012.
[1
8
]
J.
Wes
t,
“
M
u
lt
i
-
c
rit
e
ria
e
v
o
l
u
ti
o
n
a
ry
a
lg
o
rit
h
m
o
p
t
imiz
a
ti
o
n
f
o
r
h
o
rti
c
u
lt
u
re
c
r
o
p
m
a
n
a
g
e
m
e
n
t,
”
Ag
ric
.
S
y
st.
,
v
o
l.
1
7
3
,
n
o
.
Ja
n
u
a
ry
,
p
p
.
4
6
9
-
4
8
1
,
2
0
1
9
.
[1
9
]
C.
Da
i,
M
.
Ya
o
,
Z.
Xie
,
C.
Ch
e
n
,
a
n
d
J.
Li
u
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3
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Jin
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CS
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