Journal of Marine Science and Engineering,
Journal Year:
2025,
Volume and Issue:
13(5), P. 908 - 908
Published: May 3, 2025
Accurate
forecasting
of
offshore
wind
speed
is
crucial
for
the
efficient
operation
and
planning
energy
systems.
However,
inherently
non-stationary
highly
volatile
nature
speed,
coupled
with
sensitivity
neural
network-based
models
to
parameter
settings,
poses
significant
challenges.
To
address
these
issues,
this
paper
proposes
an
Adaptive
Neuro-Fuzzy
Inference
System
(ANFIS)
optimized
by
CRGWAA.
The
proposed
CRGWAA
integrates
Chebyshev
mapping
initialization,
elite-guided
reflection
refinement
operator,
a
generalized
quadratic
interpolation
strategy
enhance
population
diversity,
adaptive
exploration,
local
exploitation
capabilities.
performance
comprehensively
evaluated
on
CEC2022
benchmark
function
suite,
where
it
demonstrates
superior
optimization
accuracy,
convergence
robustness
compared
six
state-of-the-art
algorithms.
Furthermore,
ANFIS-CRGWAA
model
applied
short-term
using
real-world
data
from
region
Fujian,
China,
at
10
m
100
above
sea
level.
Experimental
results
show
that
consistently
outperforms
conventional
hybrid
baselines,
achieving
lower
MAE,
RMSE,
MAPE,
as
well
higher
R2,
across
both
altitudes.
Specifically,
original
ANFIS-WAA
model,
RMSE
reduced
approximately
45%
24%
m.
These
findings
confirm
effectiveness,
stability,
generalization
ability
complex,
prediction
tasks.
Geosciences,
Journal Year:
2025,
Volume and Issue:
15(1), P. 8 - 8
Published: Jan. 3, 2025
Noise
profoundly
affects
the
quality
of
electromagnetic
data,
and
selecting
appropriate
hyperparameters
for
machine
learning
models
poses
a
significant
challenge.
Consequently,
current
denoising
techniques
fall
short
in
delivering
precise
processing
Wide
Field
Electromagnetic
Method
(WFEM)
data.
To
eliminate
noise,
this
paper
presents
an
data
approach
based
on
improved
dung
beetle
optimized
(IDBO)
gated
recurrent
unit
(GRU)
its
application.
Firstly,
Spatial
Pyramid
Matching
(SPM)
chaotic
mapping,
variable
spiral
strategy,
Levy
flight
mechanism,
adaptive
T-distribution
variation
perturbation
strategy
were
utilized
to
enhance
DBO
algorithm.
Subsequently,
mean
square
error
is
employed
as
fitness
IDBO
algorithm
achieve
hyperparameter
optimization
GRU
Finally,
IDBO-GRU
method
applied
WFEM
Experiments
demonstrate
that
capacity
conspicuously
superior
other
intelligent
algorithms,
surpasses
probabilistic
neural
network
(PNN)
accuracy
Moreover,
time
domain
processed
more
line
with
periodic
signal
characteristics,
overall
significantly
enhanced,
electric
field
curve
stable.
Therefore,
adept
at
sequence,
application
results
also
validate
proposed
can
offer
technical
support
inversion
interpretation.
Physics of Fluids,
Journal Year:
2025,
Volume and Issue:
37(1)
Published: Jan. 1, 2025
Ultrasonic
flowmeters
are
widely
used
in
energy
and
control
applications,
providing
accurate
fast
measurement
of
fluid
flow
rates.
This
paper
proposes
a
denoising
method
based
on
the
goose
optimization
algorithm,
nature-inspired
mimicking
foraging
behavior
goose.
GO
optimizes
penalty
factor
decomposition
layer
number
variational
modal
decomposition,
resulting
GO-VMD
approach.
Decomposed
components
further
denoised
using
an
improved
wavelet
thresholding
method.
The
algorithm
is
compared
with
existing
methods,
such
as
high-frequency
ultrasonic
signal
processing,
experimental
results
show
that
it
improves
signal-to-noise
ratio
by
8%,
reduces
root
mean
square
error
5%,
retains
more
useful
information,
achieves
significant
results.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: Feb. 6, 2025
The
Snow
Goose
Algorithm
(SGA)
is
a
new
meta-heuristic
algorithm
proposed
in
2024,
which
has
been
proved
to
have
good
optimization
effect,
but
there
are
still
problems
that
easy
fall
into
local
optimal
and
premature
convergence.
In
order
further
improve
the
performance
of
algorithm,
this
paper
proposes
an
improved
(ISGA)
based
on
three
strategies
according
real
migration
habits
snow
geese:
(1)
Lead
goose
rotation
mechanism.
(2)
Honk-guiding
(3)
Outlier
boundary
strategy.
Through
above
strategies,
exploration
development
ability
original
comprehensively
enhanced,
convergence
accuracy
speed
improved.
paper,
two
standard
test
sets
IEEE
CEC2022
CEC2017
used
verify
excellent
algorithm.
practical
application
ISGA
tested
through
8
engineering
problems,
employed
enhance
effect
clustering
results
show
compared
with
comparison
faster
iteration
can
find
better
solutions,
shows
its
great
potential
solving
problems.
