Biomimetics,
Journal Year:
2024,
Volume and Issue:
9(5), P. 280 - 280
Published: May 8, 2024
The
sand
cat
swarm
optimization
algorithm
(SCSO)
is
a
novel
metaheuristic
that
has
been
proposed
in
recent
years.
optimizes
the
search
ability
of
individuals
by
mimicking
hunting
behavior
groups
nature,
thereby
achieving
robust
performance.
It
characterized
few
control
parameters
and
simple
operation.
However,
due
to
lack
population
diversity,
SCSO
less
efficient
solving
complex
problems
prone
fall
into
local
optimization.
To
address
these
shortcomings
refine
algorithm’s
efficacy,
an
improved
multi-strategy
(IMSCSO)
this
paper.
In
IMSCSO,
roulette
fitness–distance
balancing
strategy
used
select
codes
replace
random
agents
exploration
phase
enhance
convergence
performance
algorithm.
bolster
perturbation
introduced,
aiming
facilitate
escape
from
optima.
Finally,
best–worst
developed.
approach
not
only
maintains
diversity
throughout
process
but
also
enhances
exploitation
capabilities.
evaluate
we
conducted
experiments
CEC
2017
test
suite
compared
IMSCSO
with
seven
other
algorithms.
results
show
paper
better
Journal of Computational Design and Engineering,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 16, 2025
Abstract
Blasting
vibration
is
a
major
adverse
effect
in
rock
blasting
excavation,
and
accurately
predicting
its
peak
particle
velocity
(PPV)
vital
for
ensuring
engineering
safety
risk
management.
This
study
proposes
an
innovative
IHO-VMD-CatBoost
model
that
integrates
variational
mode
decomposition
(VMD)
the
CatBoost
algorithm,
with
hyperparameters
globally
optimized
using
improved
hippocampus
optimization
algorithm
(IHO).
Compared
to
existing
models,
proposed
method
improves
feature
extraction
from
signals
significantly
enhances
prediction
accuracy,
especially
complex
geological
conditions.
Using
measured
data
open-pit
mine
blasting,
extracts
key
features
such
as
maximum
section
charge,
total
horizontal
distance,
achieving
superior
performance
compared
13
traditional
models.
It
reports
root
mean
square
error
of
0.28
cm/s,
absolute
0.17
index
agreement
0.993,
variance
accounted
value
97.28%,
demonstrating
high
degree
fit
observed
data,
overall
robustness
PPV
prediction.
Additionally,
analyses
based
on
SHapley
Additive
Explanations
framework
provide
insights
into
nonlinear
relationships
between
factors
like
distance
improving
model's
interpretability.
The
demonstrates
robustness,
stability,
applicability
various
tests,
confirming
reliability
scenarios,
offering
valuable
solution
safe
mining
design.
ChemPhysMater,
Journal Year:
2023,
Volume and Issue:
unknown
Published: Oct. 1, 2023
Hydrogen,
a
clean
and
versatile
energy
carrier,
has
gained
significant
attention
as
potential
solution
for
addressing
the
challenges
of
climate
change
sustainability.
Efficient
hydrogen
production
relies
heavily
on
development
advanced
materials
that
enable
cost-effective
sustainable
methods.
This
review
article
presents
comprehensive
overview
cutting-edge
used
production,
covering
both
traditional
emerging
technologies.
begins
by
briefly
introducing
importance
carrier
various
methods
production.
emphasizes
critical
role
these
in
enabling
efficient
generation.
Traditional
methods,
such
steam
methane
reforming,
coal
gasification,
biomass
water
electrolysis,
are
discussed,
highlighting
their
advantages
limitations.
then
focuses
technologies
have
shown
promise
achieving
Photocatalytic
splitting
is
explored
with
an
emphasis
recent
advancements
semiconductor-based
photocatalysts
nanostructured
enhanced
photocatalysis.
Solid
oxide
electrolysis
cells
(SOEC)
examined,
discussing
high-temperature
electrolytes
electrode
materials.
Biological
chemical
looping
also
use
microorganisms,
bioengineered
systems,
metal
oxides
oxygen
carriers,
catalysts
improved
Advanced
characterization
techniques,
including
X-ray
diffraction,
spectroscopy,
scanning
electron
microscopy,
transmission
photoelectron
Auger
thermogravimetric
analysis,
differential
calorimetry,
been
to
gain
insight
into
properties
performances
concludes
prospects
field
highlights
durability,
stability,
cost-effectiveness,
scalability,
integration
large-scale
pchiroduction
systems.
discusses
trends
breakthroughs
could
shape
future
Engineering Applications of Artificial Intelligence,
Journal Year:
2024,
Volume and Issue:
132, P. 107932 - 107932
Published: Jan. 31, 2024
In
the
aftermath
of
natural
disasters,
efficient
waste
collection
becomes
a
crucial
challenge,
owing
to
dynamic
and
unpredictable
nature
generation,
coupled
with
resource
constraints.
This
paper
presents
an
innovative
hybrid
methodology
that
synergizes
Long
Short-Term
Memory
(LSTM)
machine
learning
Differential
Evolution
(DE)
optimisation
augment
efforts
post-disaster.
The
approach
leverages
real-time
data
forecast
generation
high
accuracy,
facilitating
development
adaptable
strategies.
Our
is
designed
dynamically
update
plans
in
response
evolving
scenarios,
ensuring
timely
effective
decision-making.
Field
tests
conducted
earthquake-prone
city
have
demonstrated
superior
performance
this
method
managing
under
fluctuating
conditions.
Moreover,
in-depth
sensitivity
analysis
helps
identifying
key
areas
for
improvement.
Significantly
outperforming
traditional
models,
offers
substantial
time
savings
equips
disaster
teams
robust
tool
addressing
challenges
collection.
Sensors,
Journal Year:
2024,
Volume and Issue:
24(10), P. 3239 - 3239
Published: May 20, 2024
The
demand
for
green
hydrogen
as
an
energy
carrier
is
projected
to
exceed
350
million
tons
per
year
by
2050,
driven
the
need
sustainable
distribution
and
storage
of
generated
from
sources.
Despite
its
potential,
production
currently
faces
challenges
related
cost
efficiency,
compliance,
monitoring,
safety.
This
work
proposes
Hydrogen
4.0,
a
cyber–physical
approach
that
leverages
Industry
4.0
technologies—including
smart
sensing,
analytics,
Internet
Things
(IoT)—to
address
these
issues
in
plants.
Such
has
potential
enhance
safety,
compliance
through
real-time
data
analysis,
predictive
maintenance,
optimised
resource
allocation,
ultimately
facilitating
adoption
renewable
hydrogen.
following
sections
break
down
conventional
plants
into
functional
blocks
discusses
how
technologies
can
be
applied
each
segment.
components,
benefits,
application
scenarios
are
discussed
while
digitalisation
contribute
successful
integration
solutions
global
sector
also
addressed.
