In
order
to
solve
the
problem
of
subtraction-average-based
optimizer
(SABO),
which
is
difficult
effectively
balance
local
development
and
global
search
capability,
golden
sine
SABO
integrating
multiple
strategies
(GSABO)
proposed.
The
improved
Sine
chaos
mapping
introduced
refine
population
initialization
strategy
in
enrich
diversity
improve
algorithm's
accuracy
speed.
position
update
method
by
algorithm
further
enhance
capability
SABO.
specific
implementation
steps
GSABO
are
described
detail,
optimization
ability
tested
using
23
benchmark
functions.
test
results
show
that
able
compared
with
current
novel
algorithms,
has
more
excellent
performance
under
most
Arabian Journal for Science and Engineering,
Год журнала:
2024,
Номер
unknown
Опубликована: Июль 1, 2024
Abstract
The
artificial
algae
algorithm
(AAA)
is
a
recently
introduced
metaheuristic
inspired
by
the
behavior
and
characteristics
of
microalgae.
Like
other
algorithms,
AAA
faces
challenges
such
as
local
optima
premature
convergence.
Various
strategies
to
address
these
issues
enhance
performance
have
been
proposed
in
literature.
These
include
levy
flight,
search,
variable
intelligent
multi-agent
systems,
quantum
behaviors.
This
paper
introduces
chaos
theory
strategy
improve
AAA's
performance.
Chaotic
maps
are
utilized
effectively
balance
exploration
exploitation,
prevent
convergence,
avoid
minima.
Ten
popular
chaotic
employed
performance,
resulting
(CAAA).
CAAA's
evaluated
on
thirty
benchmark
test
functions,
including
unimodal,
multimodal,
fixed
dimension
problems.
also
tested
three
classical
engineering
problems
eight
space
trajectory
design
at
European
Space
Agency.
A
statistical
analysis
using
Friedman
Wilcoxon
tests
confirms
that
CAA
demonstrates
successful
optimization
Mathematics,
Год журнала:
2024,
Номер
12(17), С. 2641 - 2641
Опубликована: Авг. 26, 2024
Extreme
learning
machines
(ELMs),
single
hidden-layer
feedforward
neural
networks,
are
renowned
for
their
speed
and
efficiency
in
classification
regression
tasks.
However,
generalization
ability
is
often
undermined
by
the
random
generation
of
hidden
layer
weights
biases.
To
address
this
issue,
paper
introduces
a
Hierarchical
Learning-based
Chaotic
Crayfish
Optimization
Algorithm
(HLCCOA)
aimed
at
enhancing
ELMs.
Initially,
to
resolve
problems
slow
search
premature
convergence
typical
traditional
crayfish
optimization
algorithms
(COAs),
HLCCOA
utilizes
chaotic
sequences
population
position
initialization.
The
ergodicity
chaos
leveraged
boost
diversity,
laying
groundwork
effective
global
efforts.
Additionally,
hierarchical
mechanism
encourages
under-performing
individuals
engage
extensive
cross-layer
enhanced
exploration,
while
top
performers
directly
learn
from
elite
highest
improve
local
exploitation
abilities.
Rigorous
testing
with
CEC2019
CEC2022
suites
shows
HLCCOA’s
superiority
over
both
original
COA
nine
heuristic
algorithms.
Ultimately,
HLCCOA-optimized
extreme
machine
model,
HLCCOA-ELM,
exhibits
superior
performance
reported
benchmark
models
terms
accuracy,
sensitivity,
specificity
UCI
breast
cancer
diagnosis,
underscoring
practicality
robustness,
as
well
HLCCOA-ELM’s
commendable
performance.
Journal of low frequency noise, vibration and active control,
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 30, 2024
Space
mining
robots
can
develop
and
utilize
abundant
mineral
resources
in
the
outer
space
to
solve
problem
of
depletion
earth
resources.
However,
motion
errors
complex
environments
on
surface
asteroids
greatly
hinder
its
applications.
To
bridge
this
research
gap,
a
precise
controller
robot
is
proposed
study.
Firstly,
kinematics
model
robot’s
wheels
whole
vehicle
dynamics
soft
soil
are
established.
Then,
optimal
PID
developed
based
improved
African
vultures
optimization
algorithm
(IAVOA).
The
Henon
chaotic
mapping,
nonlinear
adaptive
incremental
inertial
weight
factor
reverse
learning
competition
strategy
introduced
optimize
initial
population
position,
position
update
method
solution
output,
respectively.
Meanwhile,
excellent
performance
IAVOA
also
validated
by
test
results
nine
benchmark
functions.
Lastly,
verified
simulations
experiments.
simulation
show
that
IAVOA-PID
superior
original
AVOA-PID
with
faster
response
time
smaller
overshoot.
experiment
assistance
move
trajectory
error
less
than
0.2
m
0.01
m.
Electronics,
Год журнала:
2024,
Номер
13(19), С. 3906 - 3906
Опубликована: Окт. 2, 2024
For
effective
copyright
protection
of
digital
images,
this
paper
proposes
a
zero-watermarking
algorithm
based
on
local
image
feature
information.
The
matrix
the
is
derived
from
keypoint
set
determined
by
Speeded-Up
Robust
Features
(SURF)
algorithm,
and
it
calculates
both
gradient
descriptors
vortex-like
texture
(VTF)
set.
Unlike
traditional
descriptors,
proposed
in
contain
richer
information
exhibit
better
stability.
advantage
lies
its
ability
to
calculate
keypoints
provide
stable
vector
description
features
these
keypoints,
thereby
reducing
amount
erroneous
introduced
during
attacks.
Analysis
experimental
data
shows
that
has
good
effectiveness,
distinguishability,
security,
robustness.
Measurement Science and Technology,
Год журнала:
2024,
Номер
35(4), С. 045108 - 045108
Опубликована: Янв. 18, 2024
Abstract
The
monitoring
of
cage
longitudinal
vibration
can
directly
indicate
the
operational
status
mine
hoists.
However,
it
is
always
challenging
to
collect
sensor
signals
moving
cages
with
high
dynamic
characteristics
in
real
time
from
complex
working
environments
using
traditional
methods.
In
this
study,
a
more
practical
hybrid
signal
fusion
approach
proposed
realize
estimation
low
sampling
rate
acceleration
acquisition
and
cost
encoder
for
state
estimation.
A
nonlinear
differentiator
applied
extract
differential
expand
observation
variables.
An
unscented
Kalman
observer
based
on
hoist
model
designed
estimate
unknown
state.
To
overcome
influence
uncertain
parameters,
an
improved
evolution
(DE)
algorithm
combining
parameter
adaptive
method,
reverse
learning
competition
scheme
multiple
parallel
populations
strategy
find
parameters
autotune
algorithms
by
acceleration.
Sensor
data
simulated
experiment
platform
were
collected
processed
x
PC
system
validate
effectiveness
strategy.
experimental
results
showed
that
DE
(IDE)
had
faster
mean
tuning
smallest
fitness
value
compared
standard
DE,
particle
swarm
optimization
genetic
algorithm.
Moreover,
system,
after
IDE
algorithm,
could
achieve
purpose
estimation,
smaller
error
better
effect.
International Journal of Swarm Intelligence Research,
Год журнала:
2024,
Номер
15(1), С. 1 - 17
Опубликована: Июль 26, 2024
Firstly,
a
smart
terminal
is
designed
based
on
5G
communication
technology,
which
embedded
with
various
protection
measurement
devices
to
form
terminal.
A
distributed
control
model
for
the
distribution
network
constructed
terminals,
and
an
objective
function
taking
into
account
factors
such
as
restoring
important
loads,
surplus
power
supply
in
network,
losses,
number
of
switch
actions.
Finally,
Sparrow
Search
Algorithm
(SSA)
improved
using
elite
reverse
learning
strategy
dynamic
sine
perturbation
strategy,
it
used
solve
function.
Based
IEEE33
node
system,
experimental
tests
are
conducted,
results
show
that
average
delay
terminals
about
30ms.
Taking
14:00
example,
proposed
method
achieves
loss,
actions,
recovered
load
power,
46.39
kW,
3
times,
185.65
240.28
respectively.
The
fault
recovery
effect
ideal.
Smart Materials and Structures,
Год журнала:
2024,
Номер
33(11), С. 115032 - 115032
Опубликована: Окт. 6, 2024
Abstract
Aiming
at
the
deficiency
of
magnetic
field
utilization
rate
and
mass–torque
ratio
magnetorheological
fluid
brake
(MRB),
a
novel
MRB
is
proposed
in
this
paper.
Initially,
squeeze-shear
mode
with
multi-fluid
flow
channels
(S-MRB)
designed
its
structure
working
principle
are
described.
Based
on
analysis
circuit,
mathematical
models
established
to
describe
rotary
torque
S-MRB.
Furthermore,
COMSOL
software
carried
out
model
simulate
electromagnetic
S-MRB,
which
verified
rationality
design.
Then,
braking
mass
S-MRB
as
objective
function,
multi-objective
optimization
algorithm
adopted
optimize
structural
parameters
The
results
show
that
increased
by
25.34%
decreased
2.7%.
Finally,
performance
test
platform
established,
effectiveness
superiority
dynamic
response
characteristic
experiments.
In
order
to
solve
the
problem
of
subtraction-average-based
optimizer
(SABO),
which
is
difficult
effectively
balance
local
development
and
global
search
capability,
golden
sine
SABO
integrating
multiple
strategies
(GSABO)
proposed.
The
improved
Sine
chaos
mapping
introduced
refine
population
initialization
strategy
in
enrich
diversity
improve
algorithm's
accuracy
speed.
position
update
method
by
algorithm
further
enhance
capability
SABO.
specific
implementation
steps
GSABO
are
described
detail,
optimization
ability
tested
using
23
benchmark
functions.
test
results
show
that
able
compared
with
current
novel
algorithms,
has
more
excellent
performance
under
most
