Traditional
optimization
analysis
of
electrical
equipment
in
transmission
engineering
is
often
based
on
experience
and
rules,
lacking
intelligent
methods.
This
leads
to
limitations
the
adaptability
effectiveness
traditional
methods
when
facing
complex
variable
power
system
conditions.
By
introducing
fuzzy
neural
network
(FNN)
algorithm,
this
paper
fully
utilizes
its
nonlinear
correlations,
thereby
improving
intelligence
level
engineering.
It
collects
actual
operation
data
information
preprocesses
ensure
quality
data.
article
constructs
a
FNN
model
effectively
handle
uncertain
information,
applies
it
environment
systems.
The
experimental
results
show
that
average
RMSE
for
prediction
0.07,
optimized
voltage
very
stable.
application
algorithm
can
improve
effect
equipment.
JMIR Medical Informatics,
Год журнала:
2025,
Номер
13, С. e64349 - e64349
Опубликована: Март 6, 2025
Artificial
intelligence
(AI)
has
shown
exponential
growth
and
advancements,
revolutionizing
various
fields,
including
health
care.
However,
domain
adaptation
remains
a
significant
challenge,
as
machine
learning
(ML)
models
often
need
to
be
applied
across
different
care
settings
with
varying
patient
demographics
practices.
This
issue
is
critical
for
ensuring
effective
equitable
AI
deployment.
Cardiovascular
diseases
(CVDs),
the
leading
cause
of
global
mortality
17.9
million
annual
deaths,
encompass
conditions
like
coronary
heart
disease
hypertension.
The
increasing
availability
medical
data,
coupled
offers
new
opportunities
early
detection
intervention
in
cardiovascular
events,
leveraging
AI's
capacity
analyze
complex
datasets
uncover
patterns.
review
aims
examine
methodologies
combined
data
advance
intelligent
monitoring
CVDs,
identifying
areas
further
research
enhance
outcomes
support
interventions.
follows
PRISMA
(Preferred
Reporting
Items
Systematic
Reviews
Meta-Analyses)
methodology
ensure
rigorous
transparent
literature
process.
structured
approach
facilitated
comprehensive
overview
current
state
this
field.
Through
used,
64
documents
were
retrieved,
which
40
met
inclusion
criteria.
reviewed
papers
demonstrate
advancements
ML
CVD
detection,
classification,
prediction,
diagnosis,
monitoring.
Techniques
such
ensemble
learning,
deep
neural
networks,
feature
selection
improve
prediction
accuracy
over
traditional
methods.
predict
events
risks,
applications
via
wearable
technology.
integration
supports
personalized
treatment,
risk
assessment,
possibly
improving
management
CVDs.
study
concludes
that
techniques
can
multiple
sources
noninvasive
methods
continuous
detection.
These
help
outcomes,
indicating
potential
offer
more
precise
cost-effective
solutions
In
today's
information
age,
data
has
become
the
center
of
age
and
plays
an
important
role
in
all
industries.
Therefore,
how
to
ensure
security
focus
attention,
backup
is
one
them.
this
paper,
a
computer
remote
system
based
on
artificial
intelligence
used
realize
recovery,
which
ensures
stability
system.
Using
local
high-speed
mirroring
technology,
overall
performance
greatly
improved;
The
does
not
need
any
additional
hardware
facilities,
thus
saving
cost.
average
maintenance
cost
14,250
yuan
per
month,
that
original
28,580
month.
paper
active
recovery
after
disaster.
In
order
to
propose
a
method
of
predicting
fruit
yield
and
output
value
at
room
temperature
based
on
seasonal
time
series,
which
provides
an
important
basis
for
vegetable
industry
make
reasonable
plan,
the
stationarity
sequence
was
tested
using
ARIMA
model
test
method.
Compared
with
traditional
BP
WNN
model,
series
can
not
only
predict
number
iterations
but
also
analyze
faster,
higher
prediction
accuracy.
The
experimental
results
show
that
cycle
trend
well,
improve
accuracy
large
extent.
This
provide
production
plans
(the
average
relative
error
from
2019
2021
analysis
is
0.56%,
indicating
high
model).
In
the
context
of
rapid
development
Internet
technology,
online
education
has
become
a
trend,
which
been
liked
by
many
learners,
especially
in
college
education,
combination
and
offline
practice.
The
large
use
user
behavior
data
can
make
more
learners'
actual
situation.
Educational
assistance
plays
very
important
role
teaching.
traditional
auxiliary
mode
cannot
solve
problem
educational
Therefore,
this
paper
proposes
an
system
that
integrates
MOOC
learning
for
analysis.
First,
computer
technology
is
used
to
design
system,
indicators
are
divided
according
requirements
reduce
interference
factors
assistance.
Then,
designs
develops
teaching
forms
program,
comprehensively
analyzes
results.
MATLAB
simulation
shows
under
certain
evaluation
criteria,
integrating
better
than
terms
reliability
rationality
Computer
graphics
is
the
software
efficacy
which
majorly
utilized
in
every
social
sector
and
it
depends
on
an
existing
as
well
newly
designed
programs.
An
idea
of
computer
integrates
large
number
current
areas,
from
easy
graphic
drawing
to
design
multiple
images
actual
existence,
developing
new
projects
based
image
by
utilization
programming
tool.
The
hierarchical
clustering
most
popular
algorithm
understand
dataset
structure.
This
proposes
high-end
for
performing
Agglomerative
Hierarchical
Clustering
(AHC)
Compute
Unified
Device
Architecture
(CUDA)
NVIDIA.
research
identified
capabilities
CUDA
proposed
method
effectively
control
data
with
hardware
intense,
independent,
iterative
or
tedious
persistence
approaches
like
AHC.
efficiently
describes
greater
parallel
internally
distributed
program
experimental
results
show
attains
improved
speed
25
60
times
against
CPU
implementation
micro
array
gene
expressions.
In
mobile
communication
systems,
channel
attack
and
defense
have
always
been
one
of
the
most
important
highly
concerned
topics
in
field
wireless
interference
technology
research
application.
current
environment,
all
types
equipment
face
threats
to
varying
degrees.
This
article
is
dedicated
analyzing
discussing
how
use
side
channels
for
signal
transmission
data
collection,
also
proposes
various
methods
based
on
error
recovery
technology,
multiplexers,
etc.
deal
with
possible
loss
damage
problems
terminals.
By
evaluating
rate,
security
other
factors
sending
receiving
ends,
source
can
be
determined
whether
it
exists.
Finally,
through
system
testing
experiments,
was
verified
that
trace
number
range
original
method
156-176,
while
advanced
encryption
standard
algorithm
134-153;
training
accuracy
within
64%-79%,
Advanced
Encryption
Standard
80%-91%;
isolation
capability
0.63-0.69,
0.84-0.93.
Comprehensive
experimental
results
show
performs
very
well
aspects.
This
study
found
that
in
static
states,
the
device
can
accurately
transmit
signal
data
with
an
error
rate
below
0.5%,
packet
loss
of
2%
and
signal-to-noise
ratio
reaching
24dB.
However,
its
performance
declines
slightly
during
motion
increased
(1.2%),
(3%)
decreased
(22dB).
The
remains
around
0.8%
for
different
heart
ranges.
Moreover,
or
damage
leads
to
a
significant
increase
(5%)
(10%).
Latency
tests
also
demonstrate
device's
ability
provide
timely
health
monitoring
average
latency
10-15ms.
These
results
indicate
high
precision
reliability
interference-free
conditions,
while
further
improvements
dynamic
environments
are
needed.
comprehensive
evaluation
helps
understand
strengths
limitations
such
devices.
In
a
class,
the
role
of
management
system
is
very
important,
and
good
educational
atmosphere
can
enable
students
to
develop
learning
habits.
Ordinary
construction
methods
cannot
solve
problem
class
culture
in
management.
Therefore,
this
paper
proposes
particle
swarm
algorithm
for
analysis.
First,
computer
used
construct
cultural
management,
indicators
are
divided
according
requirements
reduce
interfering
factor.
Then,
implicitly
constructs
form
program,
carries
out
results
Comprehensive
MATLAB
simulation
shows
feasibility
under
certain
evaluation
criteria
The
rationality
better
than
ordinary
methods.
