The Risk Analysis of Cart Development Based on Dynamic Bayesian Networks
Research Square (Research Square),
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 15, 2025
Abstract
To
address
the
issues
of
multiple
uncertainties,
complex
structures,
and
unpredictability
during
development
trolley,
this
paper
proposes
a
risk
analysis
method
for
trolley
based
on
dynamic
Bayesian
networks.
First,
extensive
relevant
literature
applying
rough
set
reduction
theory
optimization,
factor
checklist
with
5
primary
indicators
16
secondary
is
constructed.
Next,
network
model
established
by
introducing
time
dimension.
Fuzzy
expert
scoring
are
used
to
quantify
probabilities
nodes,
Leaky
Noisy-or
Gate
expansion
applied
correct
conditional
probabilities.
Finally,
performed
using
bidirectional
inference
function
network.
The
time-series
variation
curve
obtained
through
case
analysis.
By
reverse
reasoning,
key
factors
occurrence
identified,
corresponding
response
strategies
proposed.
research
results
provide
new
approach
analyzing
effectively
controlling
risks
associated
development.
Язык: Английский
Fuzzy expert system design for detecting stunting
Indonesian Journal of Electrical Engineering and Computer Science,
Год журнала:
2024,
Номер
34(1), С. 556 - 556
Опубликована: Фев. 29, 2024
Stunting
is
a
chronic
nutritional
problem
that
occurs
in
toddler
due
to
lack
of
intake
which
results
impaired
growth
toddler.
Usually,
who
experience
stunting
are
characterized
by
not
increasing
weight
over
long
period
time.
Application
utilization
health
makes
it
easier
for
users
access
information,
one
can
be
used
identify
stunted
selecting
symptoms.
The
symptoms
experienced
toddlers
go
through
system
known
as
the
expert.
In
this
research
an
expert
will
developed
capable
early
detection
developmental
disorders
using
Mamdani
fuzzy
method.
obtained
from
design
method
was
implemented
group
criteria
fall
into
category
or
initial
data
still
gray
because
they
unsure
whether
categorize
having
not.
accuracy
rate
80.87%
compared
diagnosis.
Язык: Английский
Spatial Clustering of Child Malnutrition in Central Java: A Comparative Analysis Using K-Means and DBSCAN
Опубликована: Ноя. 24, 2023
The
issue
of
malnutrition
in
children
poses
a
serious
challenge
the
effort
to
achieve
well-being
and
development
smart
generation
children.
Central
Java
is
province
on
island
with
highest
prevalence
stunting,
so
efforts
for
improvement
health
intervention
planning
need
focus
areas
among
Java.
This
research
aims
identify
spatial
patterns
distribution
stunted
35
districts
cities
using
clustering
techniques.
data
used
includes
nutritional
status
all
Two
methods,
K-Means
DBSCAN,
were
applied
groups
districts/cities
stunting
characteristics.
resulted
three
clusters:
low
(11
districts/cities),
moderate
(18
high
(6
district/cities).
DBSCAN
grouped
21
into
one
main
cluster
identified
14
other
as
outliers.
In
this
study,
outperformed
higher
Silhouette
score
(0.403)
lower
Davies-Bouldin
Index
(0.785).
Язык: Английский