International journal of intelligent engineering and systems,
Год журнала:
2023,
Номер
16(3), С. 345 - 361
Опубликована: Май 1, 2023
This
research
presents
a
novel
hybrid
sampling
technique,
implemented
at
the
data
level,
to
effectively
address
imbalanced
and
noisy
in
classification
processes.The
proposed
technique
expertly
combines
two
established
methods,
namely,
random
over
(ROS)
neighbourhood
cleaning
rule
(NCL)
approaches,
tackle
imbalance
noise
issues,
respectively.The
study
carried
out
an
empirical
evaluation
of
approach
using
crowdsourced
text
that
primarily
emphasized
triple
bottom
line
(TBL)
dimension
smart
social,
economic,
environmental
city.The
used
long
short-term
memory
(LSTM),
convolutional
neural
networks
(CNN),
CNN-LSTM
models
validate
efficacy
compare
its
performance
with
other
existing
including
ROS
oversampling,
NCL
undersampling,
synthetic
minority
&
tomek
links
(SMOTE-Tomek),
oversampling
edited
nearest
neighbours
(SMOTE-ENN)
sampling.The
results
are
impressive,
ROS-NCL
achieving
high
accuracy
rates
across
all
three
models,
97.71%,
98.01%,
98.11%,
respectively.This
provides
robust
effective
solution
for
handling
impure
holds
great
promise
identifying
complex
patterns
real-world
problems.
Scientific Reports,
Год журнала:
2023,
Номер
13(1)
Опубликована: Май 31, 2023
This
paper
introduces
a
new
bio-inspired
metaheuristic
algorithm
called
Walrus
Optimization
Algorithm
(WaOA),
which
mimics
walrus
behaviors
in
nature.
The
fundamental
inspirations
employed
WaOA
design
are
the
process
of
feeding,
migrating,
escaping,
and
fighting
predators.
implementation
steps
mathematically
modeled
three
phases
exploration,
migration,
exploitation.
Sixty-eight
standard
benchmark
functions
consisting
unimodal,
high-dimensional
multimodal,
fixed-dimensional
CEC
2015
test
suite,
2017
suite
to
evaluate
performance
optimization
applications.
results
unimodal
indicate
exploitation
ability
WaOA,
multimodal
exploration
suites
high
balancing
during
search
process.
is
compared
with
ten
well-known
algorithms.
simulations
demonstrate
that
due
its
excellent
balance
exploitation,
capacity
deliver
superior
for
most
functions,
has
exhibited
remarkably
competitive
contrast
other
comparable
In
addition,
use
addressing
four
engineering
issues
twenty-two
real-world
problems
from
2011
demonstrates
apparent
effectiveness
MATLAB
codes
available
https://uk.mathworks.com/matlabcentral/profile/authors/13903104
.
Scientific Reports,
Год журнала:
2023,
Номер
13(1)
Опубликована: Март 30, 2023
Abstract
A
novel
bio-inspired
meta-heuristic
algorithm,
namely
the
American
zebra
optimization
algorithm
(AZOA),
which
mimics
social
behaviour
of
zebras
in
wild,
is
proposed
this
study.
are
distinguished
from
other
mammals
by
their
distinct
and
fascinating
character
leadership
exercise,
navies
baby
to
leave
herd
before
maturity
join
a
separate
with
no
family
ties.
This
departure
encourages
diversification
preventing
intra-family
mating.
Moreover,
convergence
assured
exercise
zebras,
directs
speed
direction
group.
lifestyle
indigenous
nature
main
inspiration
for
proposing
AZOA
algorithm.
To
examine
efficiency
CEC-2005,
CEC-2017,
CEC-2019
benchmark
functions
considered,
compared
several
state-of-the-art
algorithms.
The
experimental
outcomes
statistical
analysis
reveal
that
capable
attaining
optimal
solutions
maximum
while
maintaining
good
balance
between
exploration
exploitation.
Furthermore,
numerous
real-world
engineering
problems
have
been
employed
demonstrate
robustness
AZOA.
Finally,
it
anticipated
will
accomplish
domineeringly
forthcoming
advanced
CEC
complex
problems.
Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Фев. 11, 2024
Abstract
The
parameter
identification
problem
of
photovoltaic
(PV)
models
is
classified
as
a
complex
nonlinear
optimization
that
cannot
be
accurately
solved
by
traditional
techniques.
Therefore,
metaheuristic
algorithms
have
been
recently
used
to
solve
this
due
their
potential
approximate
the
optimal
solution
for
several
complicated
problems.
Despite
that,
existing
still
suffer
from
sluggish
convergence
rates
and
stagnation
in
local
optima
when
applied
tackle
problem.
study
presents
new
estimation
technique,
namely
HKOA,
based
on
integrating
published
Kepler
algorithm
(KOA)
with
ranking-based
update
exploitation
improvement
mechanisms
estimate
unknown
parameters
third-,
single-,
double-diode
models.
former
mechanism
aims
at
promoting
KOA’s
exploration
operator
diminish
getting
stuck
optima,
while
latter
strengthen
its
faster
converge
solution.
Both
KOA
HKOA
are
validated
using
RTC
France
solar
cell
five
PV
modules,
including
Photowatt-PWP201,
Ultra
85-P,
STP6-120/36,
STM6-40/36,
show
efficiency
stability.
In
addition,
they
extensively
compared
techniques
effectiveness.
According
experimental
findings,
strong
alternative
method
estimating
because
it
can
yield
substantially
different
superior
findings
Heliyon,
Год журнала:
2024,
Номер
10(5), С. e26665 - e26665
Опубликована: Март 1, 2024
This
research
introduces
the
Multi-Objective
Liver
Cancer
Algorithm
(MOLCA),
a
novel
approach
inspired
by
growth
and
proliferation
patterns
of
liver
tumors.
MOLCA
emulates
evolutionary
tendencies
tumors,
leveraging
their
expansion
dynamics
as
model
for
solving
multi-objective
optimization
problems
in
engineering
design.
The
algorithm
uniquely
combines
genetic
operators
with
Random
Opposition-Based
Learning
(ROBL)
strategy,
optimizing
both
local
global
search
capabilities.
Further
enhancement
is
achieved
through
integration
elitist
non-dominated
sorting
(NDS),
information
feedback
mechanism
(IFM)
Crowding
Distance
(CD)
selection
method,
which
collectively
aim
to
efficiently
identify
Pareto
optimal
front.
performance
rigorously
assessed
using
comprehensive
set
standard
test
benchmarks,
including
ZDT,
DTLZ
various
Constraint
(CONSTR,
TNK,
SRN,
BNH,
OSY
KITA)
real-world
design
like
Brushless
DC
wheel
motor,
Safety
isolating
transformer,
Helical
spring,
Two-bar
truss
Welded
beam.
Its
efficacy
benchmarked
against
prominent
algorithms
such
grey
wolf
optimizer
(NSGWO),
multiobjective
multi-verse
(MOMVO),
(NSGA-II),
decomposition-based
(MOEA/D)
marine
predator
(MOMPA).
Quantitative
analysis
conducted
GD,
IGD,
SP,
SD,
HV
RT
metrics
represent
convergence
distribution,
while
qualitative
aspects
are
presented
graphical
representations
fronts.
source
code
available
at:
https://github.com/kanak02/MOLCA.
Alexandria Engineering Journal,
Год журнала:
2024,
Номер
91, С. 348 - 367
Опубликована: Фев. 19, 2024
Honey
badger
algorithm
(HBA)
is
a
recent
swarm-based
metaheuristic
that
excels
in
simplicity
and
high
exploitation
capability.
However,
it
suffers
from
some
limitations
including
weak
exploration
capacity
an
imbalance
between
exploitation.
In
this
paper,
improved
honey
called
ODEHBA
proposed
to
improve
the
performance
of
basic
HBA.
Firstly,
orthogonal
opposition-based
learning
technique
employed
assist
population
escaping
local
optimum.
Secondly,
differential
evolution
utilized
ensure
enrichment
diversity
enhance
convergence
speed.
Finally,
capability
boosted
by
equilibrium
pool
strategy.
To
validate
efficacy
ODEHBA,
compared
with
13
well-known
algorithms
on
CEC2022
benchmark
test
sets.
Friedman
Wilcoxon
rank-sum
are
assess
ODEHBA.
Furthermore,
three
engineering
design
problems
Internet
Vehicles
(IoV)
routing
problem
applied
The
simulation
results
demonstrate
solving
complex
numerical
problems,
design,
IoV
problems.
This
holds
significant
practical
implications
for
cost
reduction
resource
utilization.
