Physica Scripta,
Journal Year:
2024,
Volume and Issue:
99(11), P. 115249 - 115249
Published: Sept. 24, 2024
Abstract
To
reduce
computational
complexity,
the
balanced
numerical
approximations
of
general
split
drift
stochastic
Runge-Kutta
methods
are
analyzed.
The
primary
reasons
for
considering
these
their
improved
stability
characteristics
and
lower
mean
square
error
compared
to
other
methods.
By
balancing
diffusion
components,
splitting
techniques
outperform
over
longer
time
increments.
For
Ito
multi-dimensional
differential
equations,
we
propose
a
novel
family
universal
procedures.
Kronecker
product
concept
is
utilized
derive
mean-square
conditions.
We
conduct
tests
evaluate
against
an
existing
weak
order
2
method.
Ultimately,
specific
example
validates
theoretical
outcomes
Physica Scripta,
Journal Year:
2025,
Volume and Issue:
100(2), P. 025230 - 025230
Published: Jan. 27, 2025
Abstract
Multi-scroll
chaos
exhibits
complex
dynamic
behavior,
the
method
of
designing
chaotic
systems
with
multi-scroll
attractor
is
an
important
research
topic.
Without
any
theoretical
guidance,
it
very
difficult
to
obtain
a
new
system,
especially
system.
In
this
paper,
class
n
-scroll
investigated
by
using
variable
transformation
based
on
th
order
polynomial
number.
The
Lyapunov
exponent,
bifurcation
diagram,
and
topological
horseshoe
in
Poincar
é
cross-section
are
presented
rigorously
prove
existence
system
assistance
computer
simulation.
Based
proposed
encryption
algorithm
for
image
information,
simulation
experiments
verify
feasibility
effectiveness
algorithm.
Mathematics,
Journal Year:
2025,
Volume and Issue:
13(6), P. 961 - 961
Published: March 14, 2025
Complex
dynamics
and
nonlinear
systems
play
a
critical
role
in
industrial
processes,
where
complex
interactions,
high
uncertainty,
external
disturbances
can
significantly
impact
efficiency,
stability,
safety.
In
sectors
such
as
mining,
manufacturing,
energy
networks,
even
small
perturbations
lead
to
unexpected
system
behaviors,
operational
inefficiencies,
or
cascading
failures.
Understanding
controlling
these
is
essential
for
developing
robust,
adaptive,
resilient
systems.
This
study
conducts
systematic
literature
review
covering
2015–2025
Scopus
Web
of
Science,
initially
retrieving
2628
(Scopus)
343
(WoS)
articles.
After
automated
filtering
(Python)
applying
inclusion/exclusion
criteria,
refined
dataset
2900
references
was
obtained,
from
which
89
highly
relevant
studies
were
selected.
The
categorized
into
six
key
areas:
(i)
heat
transfer
with
magnetized
fluids,
(ii)
control,
(iii)
big-data-driven
optimization,
(iv)
transition
via
SOEC,
(v)
fault
detection
control
valves,
(vi)
stochastic
modeling
semi-Markov
switching.
Findings
highlight
the
convergence
robust
machine
learning,
IoT,
Industry
4.0
methodologies
tackling
challenges.
Cybersecurity
sustainability
also
emerge
factors
models,
alongside
barriers
limited
data
availability,
platform
heterogeneity,
interoperability
gaps.
Future
research
should
integrate
multiscale
analysis,
deterministic
chaos,
deep
learning
enhance
adaptability,
security,
efficiency
operations
high-complexity
environments.
Physica Scripta,
Journal Year:
2024,
Volume and Issue:
99(5), P. 055225 - 055225
Published: March 25, 2024
Abstract
Involvement
of
two
capacitive
variables
into
neuron
models
provides
better
description
the
cell
membrane
property
and
then
diversity
effect
electromagnetic
field
inner
outer
can
be
estimated
in
clear
way.
Specific
electric
components
combined
to
build
equivalent
neural
circuits
for
reproducing
similar
activities
under
some
self-adaptive
control
schemes.
A
phototube
converts
external
light
stimuli
injected
energy
is
encoded
excite
membranes
presenting
suitable
firing
patterns.
Two
capacitors
are
connected
via
a
linear
resistor
mimicking
exchange
changes
potentials.
Combination
memristor
an
additive
branch
circuit
estimate
induction
absorption.
The
function
H
this
light-sensitive
memristive
calculated
theoretical
way,
average
〈
〉
predict
occurrence
stochastic
resonance,
which
confirmed
by
estimating
distribution
signal
noise
ratios.
mode
relative
value
neuron,
law
suggested
transition
adaptive
