Frontiers in Neuroinformatics,
Journal Year:
2023,
Volume and Issue:
16
Published: Jan. 16, 2023
Introduction
Atopic
dermatitis
(AD)
is
an
allergic
disease
with
extreme
itching
that
bothers
patients.
However,
diagnosing
AD
depends
on
clinicians’
subjective
judgment,
which
may
be
missed
or
misdiagnosed
sometimes.
Methods
This
paper
establishes
a
medical
prediction
model
for
the
first
time
basis
of
enhanced
particle
swarm
optimization
(SRWPSO)
algorithm
and
fuzzy
K-nearest
neighbor
(FKNN),
called
bSRWPSO-FKNN,
practiced
dataset
related
to
patients
AD.
In
SRWPSO,
Sobol
sequence
introduced
into
(PSO)
make
distribution
initial
population
more
uniform,
thus
improving
population’s
diversity
traversal.
At
same
time,
this
study
also
adds
random
replacement
strategy
adaptive
weight
updating
process
PSO
overcome
shortcomings
poor
convergence
accuracy
easily
fall
local
optimum
PSO.
core
optimize
classification
performance
FKNN
through
binary
SRWPSO.
Results
To
prove
has
scientific
significance,
successfully
demonstrates
advantages
SRWPSO
in
well-known
algorithms
benchmark
function
validation
experiments.
Secondly,
article
bSRWPSO-FKNN
practical
significance
effectiveness
nine
public
datasets.
Discussion
The
10
times
10-fold
cross-validation
experiments
demonstrate
can
pick
up
key
features
AD,
including
content
lymphocytes
(LY),
Cat
dander,
Milk,
Dermatophagoides
Pteronyssinus/Farinae,
Ragweed,
Cod,
Total
IgE.
Therefore,
established
method
practically
aids
diagnosis
Alexandria Engineering Journal,
Journal Year:
2023,
Volume and Issue:
87, P. 148 - 163
Published: Dec. 22, 2023
Vegetation
evolution
(VEGE)
is
a
newly
proposed
meta-heuristic
algorithm
(MA)
with
excellent
exploitation
but
relatively
weak
exploration
capacity.
We
thus
focus
on
further
balancing
the
and
of
VEGE
well
to
improve
overall
optimization
performance.
This
paper
proposes
an
improved
Q-learning
based
VEGE,
we
design
archive
provide
variety
search
strategies,
each
contains
four
efficient
easy-implemented
strategies.
In
addition,
online
Q-Learning,
as
ε-greedy
scheme,
are
employed
decision-maker
role
learn
knowledge
from
past
process
determine
strategy
for
individual
automatically
intelligently.
numerical
experiments,
compare
our
QVEGE
eight
state-of-the-art
MAs
including
original
CEC2020
benchmark
functions,
twelve
engineering
problems,
wireless
sensor
networks
(WSN)
coverage
problems.
Experimental
statistical
results
confirm
that
demonstrates
significant
enhancements
stands
strong
competitor
among
existing
algorithms.
The
source
code
publicly
available
at
https://github.com/RuiZhong961230/QVEGE.
International Journal of Computational Intelligence Systems,
Journal Year:
2024,
Volume and Issue:
17(1)
Published: Jan. 24, 2024
Abstract
The
Forensic-Based
Investigation
(FBI)
algorithm
is
a
novel
metaheuristic
algorithm.
Many
researches
have
shown
that
FBI
promising
due
to
two
specific
population
types.
However,
there
no
sufficient
information
exchange
between
these
types
in
the
original
Therefore,
suffers
from
many
problems.
This
paper
incorporates
self-adaptive
control
strategy
into
adjust
parameters
based
on
fitness
transformation
previous
iteration,
named
SaFBI.
In
addition
mechanism,
our
proposed
SaFBI
refers
updating
operator
further
improve
robustness
and
effectiveness
of
To
prove
availability
algorithm,
we
select
51
CEC
benchmark
functions
well-known
engineering
problems
verify
performance
Experimental
statistical
results
manifest
performs
superiorly
compared
some
state-of-the-art
algorithms.
Alexandria Engineering Journal,
Journal Year:
2023,
Volume and Issue:
81, P. 469 - 488
Published: Sept. 22, 2023
There
are
many
tricky
optimization
problems
in
real
life,
and
metaheuristic
algorithms
the
most
effective
way
to
solve
at
a
lower
cost.
The
dung
beetle
algorithm
(DBO)
is
more
innovative
proposed
2022,
which
affected
by
action
of
beetles
such
as
ball
rolling,
foraging,
reproduction.
Therefore,
A
based
on
quasi-oppositional
learning
Q-learning
(QOLDBO).
First,
quantum
state
update
idea
cleverly
integrated
into
increase
randomness
generated
population.
And
best
behavior
pattern
selected
adding
rolling
stage
improve
search
effect.
In
addition,
variable
spiral
local
domain
method
make
up
for
shortage
developing
only
around
neighborhood
optimum.
For
optimal
solution
each
iteration,
dimensional
adaptive
Gaussian
variation
retained.
Experimental
performance
tests
show
that
QOLDBO
performs
well
both
benchmark
test
functions
CEC
2017.
Simultaneously,
validity
verified
several
classical
practical
application
engineering
problems.
