2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA),
Год журнала:
2023,
Номер
unknown, С. 946 - 953
Опубликована: Ноя. 22, 2023
Cancers
are
the
most
disastrous
and
inevitable
ailment
that
occurs
in
individuals.
Due
to
hazardous
effects
of
cancer,
people
get
at
death
very
early
age.
In
today's
date,
cancer
is
categorized
into
many
types,
which
affected
by
external
internal
parts
body.
general,
cancers
caused
growth
abnormal
tissues
where
originates
it
gradually
spread
other
parts.
Therefore,
medical
industry
struggles
detect
different
types
disorders
without
any
loss
people.
Hence,
automated
detection
system
implemented
predict
its
stages
prevent
gets
worsening.
Normally,
collection
individual
data
another
challenging
concern.
Several
methods
have
been
yet
they
exist
with
constraints
provide
better
results.
Machine
learning
models
also
used,
but
does
not
tackle
big
process
fail
obtain
relevant
features.
Henceforth,
deep
model
has
emerged
for
various
processes
like
prediction,
classification,
recognition.
So,
a
new
improved
classification
framework
classifying
executed
this
paper.
At
first,
gathered
from
benchmark
database.
From
data,
genes
optimally
selected
using
an
Improved
Arithmetic
Optimization
Algorithm
(IAOA).
Then,
chosen
given
as
input
"Optimized
Deep
Neural
Network
(ODNN)"
classification.
The
DNN
optimized
AOA.
DNN,
classified
output
obtained.
Various
experimentations
carried
out
contrasting
developed
optimization
algorithm
enhanced
verify
efficient
working
suggested
model.
Throughout
result
analysis,
accuracy
precision
rate
designed
method
93.42%
9363%
all
datasets.
Archives of Computational Methods in Engineering,
Год журнала:
2023,
Номер
31(1), С. 125 - 146
Опубликована: Июль 22, 2023
Abstract
Metaheuristic
algorithms
have
applicability
in
various
fields
where
it
is
necessary
to
solve
optimization
problems.
It
has
been
a
common
practice
this
field
for
several
years
propose
new
that
take
inspiration
from
natural
and
physical
processes.
The
exponential
increase
of
controversial
issue
researchers
criticized.
However,
their
efforts
point
out
multiple
issues
involved
these
practices
insufficient
since
the
number
existing
metaheuristics
continues
yearly.
To
know
current
state
problem,
paper
analyzes
sample
111
recent
studies
so-called
new,
hybrid,
or
improved
are
proposed.
Throughout
document,
topics
reviewed
will
be
addressed
general
perspective
specific
aspects.
Among
study’s
findings,
observed
only
43%
analyzed
papers
make
some
mention
No
Free
Lunch
(NFL)
theorem,
being
significant
result
ignored
by
most
presented.
Of
studies,
65%
present
an
version
established
algorithm,
which
reveals
trend
no
longer
based
on
analogies.
Additionally,
compilation
solutions
found
engineering
problems
commonly
used
verify
performance
state-of-the-art
demonstrate
with
low
level
innovation
can
erroneously
considered
as
frameworks
years,
known
Black
Widow
Optimization
Coral
Reef
analyzed.
study
its
components
they
do
not
any
innovation.
Instead,
just
deficient
mixtures
different
evolutionary
operators.
This
applies
extension
recently
proposed
versions.
Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Март 30, 2024
Abstract
To
address
the
issues
of
lacking
ability,
loss
population
diversity,
and
tendency
to
fall
into
local
extreme
value
in
later
stage
optimization
searching,
resulting
slow
convergence
lack
exploration
ability
artificial
gorilla
troops
optimizer
algorithm
(AGTO),
this
paper
proposes
a
search
that
integrates
positive
cosine
Cauchy's
variance
(SCAGTO).
Firstly,
is
initialized
using
refractive
reverse
learning
mechanism
increase
species
diversity.
A
strategy
nonlinearly
decreasing
weight
factors
are
introduced
finder
position
update
coordinate
global
algorithm.
The
follower
updated
by
introducing
Cauchy
variation
perturb
optimal
solution,
thereby
improving
algorithm's
obtain
solution.
SCAGTO
evaluated
30
classical
test
functions
Test
Functions
2018
terms
speed,
accuracy,
average
absolute
error,
other
indexes,
two
engineering
design
problems,
namely,
pressure
vessel
problem
welded
beam
problem,
for
verification.
experimental
results
demonstrate
improved
significantly
enhances
speed
exhibits
good
robustness.
demonstrates
certain
solution
advantages
optimizing
verifying
superior
practicality
Applied Sciences,
Год журнала:
2025,
Номер
15(4), С. 1907 - 1907
Опубликована: Фев. 12, 2025
Multi-object
tracking
(MOT)
is
an
important
task
in
computer
vision,
particularly
complex,
dynamic
environments
with
crowded
scenes
and
frequent
occlusions.
Traditional
methods
often
suffer
from
identity
switches
(IDSws)
fragmented
tracks
(FMs),
which
limits
their
ability
to
maintain
consistent
object
trajectories.
In
this
paper,
we
present
a
novel
framework,
called
ReTrackVLM,
that
integrates
multimodal
embedding
visual
language
model
(VLM)
zero-shot
re-identification
(ReID)
module
enhance
accuracy
robustness.
ReTrackVLM
leverages
the
rich
semantic
information
VLMs
distinguish
objects
more
effectively,
even
under
challenging
conditions,
while
ReID
mechanism
enables
robust
matching
without
additional
training.
The
system
also
includes
motion
prediction
module,
powered
by
Kalman
filtering,
handle
occlusions
abrupt
movements.
We
evaluated
on
several
widely
used
MOT
benchmarks,
including
MOT15,
MOT16,
MOT17,
MOT20,
DanceTrack.
Our
approach
achieves
state-of-the-art
results,
improvements
of
1.5%
MOTA
reduction
10.
3%
IDSws
compared
existing
methods.
excels
precision,
recording
91.7%
precision
MOT17.
However,
extremely
dense
scenes,
framework
faces
challenges
slight
increases
IDSws.
Despite
computational
overhead
using
VLMs,
demonstrates
track
effectively
diverse
scenarios.
Electronics,
Год журнала:
2023,
Номер
12(4), С. 1058 - 1058
Опубликована: Фев. 20, 2023
Multilevel
inverters
(MLI)
are
popular
in
high-power
applications.
MLIs
generally
configured
to
have
switches
reduced
by
switching
techniques
that
eliminate
low-order
harmonics.
The
selective
harmonic
elimination
(SHE)
method,
which
significantly
reduces
the
number
of
switching,
determines
optimal
moments
obtain
desired
output
voltage
and
eliminates
components.
To
solve
SHE
problem,
classical
methods
primarily
employed.
disadvantages
such
high
probability
trapping
locally
solutions
their
dependence
on
initial
controlling
parameters.
One
solution
overcome
this
problem
is
use
metaheuristic
algorithms.
In
study,
firstly,
22
algorithms
with
different
sources
inspiration
were
used
at
levels
MLIs,
performances
extensively
analyzed.
reveal
method
offers
best
solution,
these
first
applied
an
11-level
MLI
circuit,
six
determined
as
a
result
performance
analysis.
As
evaluation,
outstanding
SPBO,
BMO,
GA,
GWO,
MFO,
SPSA.
application
superior
7-,
11-,
15-,
19-level
according
IEEE
519—2014
standard,
it
has
been
shown
BMO
outperforms
7-level
MLI,
GA
SPBO
15-
terms
THD,
while
quality,
SPSA
15-level
come
forward.
Journal Européen des Systèmes Automatisés,
Год журнала:
2024,
Номер
57(2), С. 417 - 424
Опубликована: Апрель 28, 2024
An
active
magnetic
bearing
(AMB)
is
a
frictionless
used
in
high-speed
motors
and
other
electromechanical
products.Due
to
its
open
loop
instability,
utilization
of
controller
essential
stabilize
the
system.In
this
paper,
comparative
study
between
sliding
mode
control
(SMC)
back-stepping
(BSC)
are
presented
for
AMB
systems.These
two
techniques
have
been
applied
various
dynamical
systems
obtain
stable
systems.On
basis
avoiding
chattering
SMC
design,
power
rate
reaching
introduced
design
action
SMC.In
terms
BSC
Lyapunov-stability
theorem
utilized
derive
low
controller.A
gorilla
troops
optimization
(GTO)
has
tune
adjustable
parameters
proposed
controllers.According
computer
simulation
based
on
MATLAB
software,
results
indicate
superior
performance
improved
system
response
as
compared
controller.In
addition,
strategy
good
disturbance
rejection
capability
strategy.
Artificial Intelligence Review,
Год журнала:
2024,
Номер
57(9)
Опубликована: Авг. 12, 2024
Abstract
A
recently
developed
algorithm
inspired
by
natural
processes,
known
as
the
Artificial
Gorilla
Troops
Optimizer
(GTO),
boasts
a
straightforward
structure,
unique
stabilizing
features,
and
notably
high
effectiveness.
Its
primary
objective
is
to
efficiently
find
solutions
for
wide
array
of
challenges,
whether
they
involve
constraints
or
not.
The
GTO
takes
its
inspiration
from
behavior
in
world.
To
emulate
impact
gorillas
at
each
stage
search
process,
employs
flexible
weighting
mechanism
rooted
concept.
exceptional
qualities,
including
independence
derivatives,
lack
parameters,
user-friendliness,
adaptability,
simplicity,
have
resulted
rapid
adoption
addressing
various
optimization
challenges.
This
review
dedicated
examination
discussion
foundational
research
that
forms
basis
GTO.
It
delves
into
evolution
this
algorithm,
drawing
insights
112
studies
highlight
Additionally,
it
explores
proposed
enhancements
GTO’s
behavior,
with
specific
focus
on
aligning
geometry
area
real-world
problems.
also
introduces
solver,
providing
details
about
identification
organization,
demonstrates
application
scenarios.
Furthermore,
provides
critical
assessment
convergence
while
limitation
In
conclusion,
summarizes
key
findings
study
suggests
potential
avenues
future
advancements
adaptations
related
Abstract
In
recent
decades,
the
rapid
growth
of
Internet
Things
(IoT)
has
highlighted
several
network
security
problems.
this
study,
an
efficient
intrusion
detection
(ID)
system
is
implemented
by
using
both
machine
learning
and
data
mining
concepts
for
detecting
patterns.
During
initial
phase,
are
collected
from
NSL‐KDD
University
New
South
Wales‐Network
Based
15
(UNSW‐NB15)
datasets.
The
then
normalized/scaled
employing
a
standard
scaler
technique.
Next,
informative
feature
values
selected
proposed
optimization
algorithm—that
is,
Niche‐Strategy‐based
Gorilla
Troops
Optimization
(NSGTO)
algorithm.
Finally,
these
transferred
to
Long
Short‐Term
Memory
(LSTM)
model
classify
types
attacks
on
comparison
existing
ID
systems,
based
NSGTO‐LSTM
obtains
classification
accuracy
99.98%
99.90%