With
the
exponential
growth
of
digital
data,
recommendation
systems
or
recommender
are
widely
used
in
various
domains
assisting
users
filtering
and
decision-making
on
massive
information.
Recommendation
capable
delivering
personalized
content
to
enhance
user
experience
satisfaction
through
users'
preferences
behaviors.
The
machine
learning
algorithms
employed
facilitate
effectiveness
tasks
achieved
by
those
among
which,
for
example,
is
providing
accurate
prediction
that
matches
preferences.
Swarm
Intelligence
offers
robust
optimization
mechanisms
have
been
successfully
applied
computational
problems
including
refining
algorithms.
To
best
our
knowledge,
there
no
recent
comprehensive
survey
swarm
intelligence
optimizing
techniques
when
systems.
Therefore,
this
presents
a
We
conducted
literature
intelligence,
using
relevant
keywords
their
variants,
focusing
publications
since
2019.
Our
findings
highlight
use
primarily
clustering,
classification,
feature
selection
has
significantly
enhanced
systems,
especially
clustering
classification.
However,
balance
between
complexity
processing
speed
remains
challenge.
Future
research
could
focus
these
better
efficiency
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: Feb. 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
Energy Reports,
Journal Year:
2024,
Volume and Issue:
11, P. 5252 - 5270
Published: May 15, 2024
Inspired
by
the
fact
that
Special
Trans
Function
(STF)
is
more
accurate
than
Lambert
W
function
(LWF),
this
paper
rigorously
derives
two
types
of
STF-based
exact
expressions
for
double-diode
model
(DDM)
and
triple-diode
(TDM)
solar
cells.
The
former
involves
multi-STF
(mSTF),
while
latter
contains
single-STF
(sSTF),
bridging
remaining
gap
in
describing
nonlinear
I–V
characteristic
cells
using
STF.
proposed
mSTF
sSTF
are
closely
linked
with
but
different
from
multi-Lambert
(mLWF),
single-LWF
(sLWF)
implicit
exponential
(IEF)
based
expressions,
particularly
terms
fitness
parameter
extraction.
Through
a
test
involving
203
cases
space
STF
branch
x∈R+,
it
was
found
under
same
values,
consistently
outperforms
fitting
measured
data
various
cell/modules,
followed
sSTF,
mLWF,
sLWF,
finally
IEF-based
expression.
Notably,
all
optimal
x
fall
within
interval
x∈[0,6]
rather
preset
x∈[0,20].
A
normalized
trust-region-reflective
(NTRR)
algorithm
V-shaped
selection
strategy
developed
to
improve
extraction
sSTF.
Results
derivative-dependent
NTRR
population-based
Rcr-IJADE
indicate
achieves
highest
accuracy
fastest
convergence
speed,
mSTF,
mLWF
Moreover,
exhibits
fewer
degeneracies
TDM
DDM
compared
other
expressions.
Given
these
advantages,
show
great
promise
PV
simulation
therefore
deserve
serious
attention.
Expert Systems with Applications,
Journal Year:
2024,
Volume and Issue:
255, P. 124777 - 124777
Published: July 14, 2024
Accurately
estimating
the
unknown
parameters
of
photovoltaic
(PV)
models
based
on
measured
voltage-current
data
is
a
challenging
optimization
problem
due
to
its
high
nonlinearity
and
multimodality.
An
accurate
solution
this
essential
for
efficiently
simulating,
controlling,
evaluating
PV
systems.
There
are
three
different
models,
including
single-diode
model,
double-diode
triple-diode
with
five,
seven,
nine
parameters,
respectively,
proposed
represent
electrical
characteristics
systems
varying
levels
complexity
accuracy.
In
literature,
several
deterministic
metaheuristic
algorithms
have
been
used
accurately
solve
hard
problem.
However,
problem,
methods
could
not
achieve
solutions.
On
other
side,
algorithms,
also
known
as
gradient-free
methods,
somewhat
good
solutions
but
they
still
need
further
improvements
strengthen
their
performance
against
stuck-in
local
optima
slow
convergence
speed
problems.
Over
last
two
years,
recent
better
improve
avoid
tackle
continuous
majority
those
has
investigated.
Therefore,
in
paper,
nineteen
recently
published
such
Mantis
search
algorithm
(MSA),
spider
wasp
optimizer
(SWO),
light
spectrum
(LSO),
growth
(GO),
walrus
(WAOA),
hippopotamus
(HOA),
black-winged
kite
(BKA),
quadratic
interpolation
(QIO),
sinh
cosh
(SCHA),
exponential
distribution
(EDO),
optical
microscope
(OMA),
secretary
bird
(SBOA),
Parrot
Optimizer
(PO),
Newton-Raphson-based
(NRBO),
crested
porcupine
(CPO),
differentiated
creative
(DCS),
propagation
(PSA),
one-to-one
(OOBO),
triangulation
topology
aggregation
(TTAO),
studied
clarify
effectiveness
models.
addition,
collaborate
functions,
namely
Lambert
W-Function
Newton-Raphson
Method,
aid
solving
I-V
curve
equations
more
accurately,
thereby
improving
Those
assessed
using
four
well-known
solar
cells
modules
compared
each
metrics,
best
fitness,
average
worst
standard
deviation
(SD),
Friedman
mean
rank,
speed;
multiple-comparison
test
compare
difference
between
ranks.
Results
comparison
show
that
SWO
efficient
effective
SDM,
DDM,
TDM
over
modules,
Method
equations.
study
reports
perform
poorly
when
applied
Journal of King Saud University - Computer and Information Sciences,
Journal Year:
2024,
Volume and Issue:
36(7), P. 102132 - 102132
Published: July 20, 2024
The
widespread
integration
of
software
into
all
parts
our
lives
has
led
to
the
need
for
higher
reliability.
Ensuring
reliable
usually
necessitates
some
form
formal
methods
in
early
stages
development
process
which
requires
strenuous
effort.
Hence,
researchers
field
reliability
introduced
Software
Reliability
Growth
Models
(SRGMs)
as
a
relatively
inexpensive
approach
prediction.
Conventional
parameter
estimation
SRGMs
were
ineffective
and
left
more
be
desired.
Consequently,
sought
out
swarm
intelligence
combat
its
flaws,
resulting
significant
improvements.
While
similar
surveys
exist
within
domain,
are
broader
scope
do
not
cover
many
algorithms.
Moreover,
resulted
occasional
omission
information
regarding
design
predictions.
A
comprehensive
survey
containing
38
studies
18
different
algorithms
domain
is
presented.
Each
proposed
by
was
systematically
analyzed
where
relevant
including
measures
used,
datasets
effectiveness
each
design,
extracted
organized
tables
taxonomies
able
identify
current
trends
domain.
Some
notable
findings
include
distance-based
providing
high
prediction
accuracy
an
increasing
trend
hybridized
variants
designs
predict
Future
encouraged
Mean
Square
Error
(MSE)
or
Root
MSE
offer
largest
sample
size
comparison.
Artificial Intelligence Review,
Journal Year:
2024,
Volume and Issue:
57(9)
Published: Aug. 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
PeerJ Computer Science,
Journal Year:
2025,
Volume and Issue:
11, P. e2646 - e2646
Published: Jan. 27, 2025
This
study
conducts
a
comparative
analysis
of
the
performance
ten
novel
and
well-performing
metaheuristic
algorithms
for
parameter
estimation
solar
photovoltaic
models.
optimization
problem
involves
accurately
identifying
parameters
that
reflect
complex
nonlinear
behaviours
cells
affected
by
changing
environmental
conditions
material
inconsistencies.
is
challenging
due
to
computational
complexity
risk
errors,
which
can
hinder
reliable
predictions.
The
evaluated
include
Crayfish
Optimization
Algorithm,
Golf
Coati
Crested
Porcupine
Optimizer,
Growth
Artificial
Protozoa
Secretary
Bird
Mother
Election
Optimizer
Technical
Vocational
Education
Training-Based
Optimizer.
These
are
applied
solve
four
well-established
models:
single-diode
model,
double-diode
triple-diode
different
module
focuses
on
key
metrics
such
as
execution
time,
number
function
evaluations,
solution
optimality.
results
reveal
significant
differences
in
efficiency
accuracy
algorithms,
with
some
demonstrating
superior
specific
Friedman
test
was
utilized
rank
various
revealing
top
performer
across
all
considered
optimizer
achieved
root
mean
square
error
9.8602187789E-04
9.8248487610E-04
both
models
1.2307306856E-02
model.
consistent
success
indicates
strong
contender
future
enhancements
aimed
at
further
boosting
its
effectiveness.
Its
current
suggests
potential
improvement,
making
it
promising
focus
ongoing
development
efforts.
findings
contribute
understanding
applicability
renewable
energy
systems,
providing
valuable
insights
optimizing
