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1
Modeling Uncertainty with Fuzzy Logic: With Recent Theory and Applications
Springer-Verlag Berlin Heidelberg
Asli Celikyilmaz
,
I. Burhan Türksen (auth.)
fuzzy
functions
values
membership
function
parameters
cluster
clustering
models
optimum
dataset
algorithm
method
output
regression
ifc
input
sets
methods
validation
systems
interval
proposed
datasets
clusters
vector
classification
t1iff
testing
linear
inference
algorithms
uncertainty
svm
obtained
structures
modeling
stock
variables
fcm
identified
figure
edit2iff
approach
experiments
identify
et1iff
average
shown
interim
Godina:
2009
Jezik:
english
Fajl:
PDF, 11.49 MB
Vaši tagovi:
0
/
0
english, 2009
2
Modeling Uncertainty with Fuzzy Logic: With Recent Theory and Applications
Springer-Verlag Berlin Heidelberg
Asli Celikyilmaz
,
I. Burhan Türksen (auth.)
fuzzy
functions
values
membership
function
parameters
cluster
clustering
models
optimum
dataset
algorithm
method
output
regression
ifc
input
sets
methods
validation
systems
interval
proposed
datasets
clusters
vector
classification
t1iff
testing
linear
inference
algorithms
uncertainty
svm
obtained
structures
modeling
stock
variables
fcm
identified
figure
edit2iff
approach
experiments
identify
et1iff
average
shown
interim
Godina:
2009
Jezik:
english
Fajl:
PDF, 10.74 MB
Vaši tagovi:
0
/
0
english, 2009
3
Modeling uncertainty with fuzzy logic: with recent theory and applications
Springer-Verlag Berlin Heidelberg
Asli Celikyilmaz
,
I. Burhan Türksen (auth.)
fuzzy
functions
values
membership
function
parameters
cluster
clustering
models
optimum
dataset
algorithm
method
output
regression
ifc
input
sets
methods
validation
systems
interval
proposed
datasets
clusters
vector
classification
t1iff
testing
linear
inference
algorithms
uncertainty
svm
obtained
structures
modeling
stock
variables
fcm
identified
figure
edit2iff
approach
experiments
identify
et1iff
average
shown
interim
Godina:
2009
Jezik:
english
Fajl:
PDF, 10.73 MB
Vaši tagovi:
0
/
0
english, 2009
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