Water,
Journal Year:
2023,
Volume and Issue:
15(3), P. 486 - 486
Published: Jan. 25, 2023
Modeling
potential
evapotranspiration
(ET0)
is
an
important
issue
for
water
resources
planning
and
management
projects
involving
droughts
flood
hazards.
Evapotranspiration,
one
of
the
main
components
hydrological
cycle,
highly
effective
in
drought
monitoring.
This
study
investigates
efficiency
two
machine-learning
methods,
random
vector
functional
link
(RVFL)
relevance
machine
(RVM),
improved
with
new
metaheuristic
algorithms,
quantum-based
avian
navigation
optimizer
algorithm
(QANA),
artificial
hummingbird
(AHA)
modeling
ET0
using
limited
climatic
data,
minimum
temperature,
maximum
extraterrestrial
radiation.
The
outcomes
hybrid
RVFL-AHA,
RVFL-QANA,
RVM-AHA,
RVM-QANA
models
compared
single
RVFL
RVM
models.
Various
input
combinations
three
data
split
scenarios
were
employed.
results
revealed
that
AHA
QANA
considerably
methods
ET0.
Considering
periodicity
component
radiation
as
inputs
prediction
accuracy
applied
methods.
Mathematics,
Journal Year:
2022,
Volume and Issue:
10(19), P. 3466 - 3466
Published: Sept. 23, 2022
This
paper
introduces
a
novel
physical-inspired
metaheuristic
algorithm
called
“Light
Spectrum
Optimizer
(LSO)”
for
continuous
optimization
problems.
The
inspiration
the
proposed
is
light
dispersions
with
different
angles
while
passing
through
rain
droplets,
causing
meteorological
phenomenon
of
colorful
rainbow
spectrum.
In
order
to
validate
algorithm,
three
experiments
are
conducted.
First,
LSO
tested
on
solving
CEC
2005,
and
obtained
results
compared
wide
range
well-regarded
metaheuristics.
second
experiment,
used
four
competitions
in
single
objective
benchmarks
(CEC2014,
CEC2017,
CEC2020,
CEC2022),
its
eleven
well-established
recently-published
optimizers,
named
grey
wolf
optimizer
(GWO),
whale
(WOA),
salp
swarm
(SSA),
evolutionary
algorithms
like
differential
evolution
(DE),
optimizers
including
gradient-based
(GBO),
artificial
gorilla
troops
(GTO),
Runge–Kutta
method
(RUN)
beyond
metaphor,
African
vultures
(AVOA),
equilibrium
(EO),
Reptile
Search
Algorithm
(RSA),
slime
mold
(SMA).
addition,
several
engineering
design
problems
solved,
many
from
literature.
experimental
statistical
analysis
demonstrate
merits
highly
superior
performance
algorithm.
Electronics,
Journal Year:
2022,
Volume and Issue:
11(22), P. 3798 - 3798
Published: Nov. 18, 2022
Developing
countries
have
had
numerous
obstacles
in
diagnosing
the
COVID-19
worldwide
pandemic
since
its
emergence.
One
of
most
important
ways
to
control
spread
this
disease
begins
with
early
detection,
which
allows
that
isolation
and
treatment
could
perhaps
be
started.
According
recent
results,
chest
X-ray
scans
provide
information
about
onset
infection,
may
evaluated
so
diagnosis
can
begin
sooner.
This
is
where
artificial
intelligence
collides
skilled
clinicians’
diagnostic
abilities.
The
suggested
study’s
goal
make
a
contribution
battling
epidemic
by
using
simple
convolutional
neural
network
(CNN)
model
construct
an
automated
image
analysis
framework
for
recognizing
afflicted
data.
To
improve
classification
accuracy,
fully
connected
layers
CNN
were
replaced
efficient
extreme
gradient
boosting
(XGBoost)
classifier,
used
categorize
extracted
features
layers.
Additionally,
hybrid
version
arithmetic
optimization
algorithm
(AOA),
also
developed
facilitate
proposed
research,
tune
XGBoost
hyperparameters
images.
Reported
experimental
data
showed
approach
outperforms
other
state-of-the-art
methods,
including
cutting-edge
metaheuristics
algorithms,
tested
same
framework.
For
validation
purposes,
balanced
images
dataset
12,000
observations,
belonging
normal,
viral
pneumonia
classes,
was
used.
method,
tuned
introduced
AOA,
superior
performance,
achieving
accuracy
approximately
99.39%
weighted
average
precision,
recall
F1-score
0.993889,
0.993887
0.993887,
respectively.
Artificial Intelligence Review,
Journal Year:
2024,
Volume and Issue:
57(4)
Published: March 23, 2024
Abstract
This
paper
innovatively
proposes
the
Black
Kite
Algorithm
(BKA),
a
meta-heuristic
optimization
algorithm
inspired
by
migratory
and
predatory
behavior
of
black
kite.
The
BKA
integrates
Cauchy
mutation
strategy
Leader
to
enhance
global
search
capability
convergence
speed
algorithm.
novel
combination
achieves
good
balance
between
exploring
solutions
utilizing
local
information.
Against
standard
test
function
sets
CEC-2022
CEC-2017,
as
well
other
complex
functions,
attained
best
performance
in
66.7,
72.4
77.8%
cases,
respectively.
effectiveness
is
validated
through
detailed
analysis
statistical
comparisons.
Moreover,
its
application
solving
five
practical
engineering
design
problems
demonstrates
potential
addressing
constrained
challenges
real
world
indicates
that
it
has
significant
competitive
strength
comparison
with
existing
techniques.
In
summary,
proven
value
advantages
variety
due
excellent
performance.
source
code
publicly
available
at
https://www.mathworks.com/matlabcentral/fileexchange/161401-black-winged-kite-algorithm-bka
.
Sensors,
Journal Year:
2022,
Volume and Issue:
22(4), P. 1410 - 1410
Published: Feb. 12, 2022
Bearings
are
widely
used
in
various
electrical
and
mechanical
equipment.
As
their
core
components,
failures
often
have
serious
consequences.
At
present,
most
parameter
adjustment
methods
still
manual
adjustments
of
parameters.
This
method
is
easily
affected
by
prior
knowledge,
falls
into
the
local
optimal
solution,
cannot
obtain
global
requires
a
lot
resources.
Therefore,
this
paper
proposes
new
for
bearing
fault
diagnosis
based
on
wavelet
packet
transform
convolutional
neural
network
optimized
simulated
annealing
algorithm.
Firstly,
original
vibration
signal
extracted
to
spectrogram,
then
obtained
spectrogram
sent
adjustment,
finally
algorithm
adjust
To
verify
effectiveness
method,
database
Case
Western
Reserve
University
testing,
traditional
intelligent
compared.
The
results
show
that
proposed
has
better
more
reliable
effect
than
existing
machine
learning
deep
methods.
