MSAO: A multi-strategy boosted snow ablation optimizer for global optimization and real-world engineering applications
Advanced Engineering Informatics,
Год журнала:
2024,
Номер
61, С. 102464 - 102464
Опубликована: Март 15, 2024
Язык: Английский
Generative Early Architectural Visualizations: Incorporating Architect's Style-trained Models
Journal of Computational Design and Engineering,
Год журнала:
2024,
Номер
11(5), С. 40 - 59
Опубликована: Июль 15, 2024
Abstract
This
study
introduces
a
novel
approach
to
architectural
visualization
using
generative
artificial
intelligence
(AI),
particularly
emphasizing
text-to-image
technology,
remarkably
improve
the
process
right
from
initial
design
phase
within
architecture,
engineering,
and
construction
industry.
By
creating
more
than
10
000
images
incorporating
an
architect’s
personal
style
characteristics
into
residential
house
model,
effectiveness
of
base
AI
models.
Furthermore,
various
styles
were
integrated
enhance
process.
method
involved
additional
training
for
with
low
similarity
rates,
which
required
extensive
data
preparation
their
integration
model.
Demonstrated
be
effective
across
multiple
scenarios,
this
technique
markedly
enhances
efficiency
speed
production
images.
Highlighting
vast
potential
in
visualization,
our
emphasizes
technology’s
shift
toward
facilitating
user-centered
personalized
applications.
Язык: Английский
A multi-threshold image segmentation method based on arithmetic optimization algorithm: A real case with skin cancer dermoscopic images
Journal of Computational Design and Engineering,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 14, 2025
Abstract
Multi-threshold
image
segmentation
(MTIS)
is
a
crucial
technology
in
processing,
characterized
by
simplicity
and
efficiency,
the
key
lies
selection
of
thresholds.
However,
method's
time
complexity
will
grow
exponentially
with
number
To
solve
this
problem,
an
improved
arithmetic
optimization
algorithm
(ETAOA)
proposed
paper,
optimizer
for
optimizing
process
merging
appropriate
Specifically,
two
strategies
are
introduced
to
optimize
optimal
threshold
process:
elite
evolutionary
strategy
(EES)
tracking
(ETS).
First,
verify
performance
ETAOA,
mechanism
comparison
experiments,
scalability
tests,
experiments
nine
state-of-the-art
peers
executed
based
on
benchmark
functions
CEC2014
CEC2022.
After
that,
demonstrate
feasibility
ETAOA
domain,
were
performed
using
ten
advanced
methods
skin
cancer
dermatoscopy
datasets
under
low
high
thresholds,
respectively.
The
above
experimental
results
show
that
performs
outstanding
compared
functions.
Moreover,
domain
has
superior
conditions.
Язык: Английский
Image Segmentation Technology Based on Ant Colony Algorithm
Deleted Journal,
Год журнала:
2024,
Номер
20(7s), С. 1038 - 1042
Опубликована: Май 4, 2024
Image
segmentation
is
a
key
task
in
computer
vision,
with
applications
ranging
from
medical
diagnosis
to
autonomous
driving.
The
Ant
Colony
Algorithm
(ACO),
modeled
after
ant
foraging
behavior,
has
emerged
as
viable
methodology.
However,
ACO-based
algorithms
frequently
generate
segmented
outputs
jagged
or
uneven
boundaries,
which
reduces
their
interpretability
and
usability.
To
alleviate
this
problem,
they
study
the
use
of
boundary-smoothing
approaches
segmentation.
In
paper,
investigate
image
technology
based
on
Algorithm,
focus
border
smoothing.
They
examine
fundamentals
ACO
its
application
segmentation,
emphasizing
strengths
limits.
also
look
at
several
boundary
smoothing
strategies,
such
morphological
operations,
edge-preserving
filters,
active
contours
(snakes),
how
affect
performance.
Through
experimental
validation
comparative
analysis,
show
that
improves
accuracy
visual
quality
images
produced
by
algorithms.
These
results
help
design
more
robust
visually
appealing
algorithms,
have
potential
imaging,
remote
sensing,
industrial
automation.
Язык: Английский
Optimizing Microseismic Monitoring: A Fusion of Gaussian-Cauchy and Adaptive Weight Strategies
Journal of Computational Design and Engineering,
Год журнала:
2024,
Номер
11(5), С. 1 - 28
Опубликована: Авг. 8, 2024
Abstract
In
mining
mineral
resources,
it
is
vital
to
monitor
the
stability
of
rock
body
in
real
time,
reasonably
regulate
area
ground
pressure
concentration,
and
guarantee
safety
personnel
equipment.
The
microseismic
signals
generated
by
monitoring
rupture
can
effectively
predict
disaster,
but
current
technology
not
ideal.
order
address
issue
deep
wells,
this
research
suggests
a
machine
learning-based
model
for
predicting
phenomena.
First,
work
presents
random
spare,
double
adaptive
weight,
Gaussian–Cauchy
fusion
strategies
as
additions
multi-verse
optimizer
(MVO)
an
enhanced
MVO
algorithm
(RDGMVO).
Subsequently,
RDGMVO-Fuzzy
K-Nearest
Neighbours
(RDGMVO-FKNN)
prediction
presented
combining
with
FKNN
classifier.
experimental
section
compares
12
traditional
recently
algorithms
RDGMVO,
demonstrating
latter’s
excellent
benchmark
optimization
performance
remarkable
improvement
effect.
Next,
comparison
experiment,
classical
classifier
dataset
feature
selection
experiment
confirm
precision
RDGMVO-FKNN
problem.
According
results,
has
accuracy
above
89%,
indicating
that
reliable
accurate
method
classifying
occurrences.
Code
been
available
at
https://github.com/GuaipiXiao/RDGMVO.
Язык: Английский
CMLsearch: Semantic Visual Search and Simulation through Segmented Color, Material, and Lighting in Interior Image
Journal of Computational Design and Engineering,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 30, 2024
Abstract
In
product
search
systems,
user
behavior
changes
according
to
their
intentions,
requiring
adaptations
in
system
requirements
and
information
modeling.
When
purchasing
home
decor
products,
users
must
consider
existing
setting
(EHS)
the
need
pair
multiple
elements,
not
just
a
single
product.
However,
no
systems
assist
with
varied
intents
(Target-Finding
Decision-Making
scenarios),
nor
have
they
focused
on
research
that
helps
various
elements
of
user's
setting.
Therefore,
we
introduce
CMLsearch:
semantic
visual
segments
color,
material,
lighting,
includes
light
CCT
simulation.
study
(N
=
44),
CMLsearch
significantly
improved
satisfaction
decisions
compared
conventional
systems.
The
reflected
intent,
offering
object-level
control
supported
more
searches
target-finding
scenarios
broader
exploration
decision-making
scenarios.
simulation
further
boosted
confidence
by
allowing
visualize
products
under
different
lighting
conditions.
Язык: Английский