Transactions on Economics Business and Management Research,
Год журнала:
2023,
Номер
3, С. 64 - 71
Опубликована: Дек. 25, 2023
This
study
delves
into
the
challenges
and
complexities
of
vegetable
sales
management
in
modern
commercial
environments,
particularly
fresh
food
supermarkets.
By
utilizing
descriptive
statistics
visual
analysis
data,
reveals
correlations
between
different
categories
quantifies
these
using
Pearson's
correlation
coefficient.
Subsequently,
by
integrating
time
series
multi-objective
programming,
a
mathematical
model
is
constructed,
aimed
at
maximizing
profits
under
specific
constraints.
The
innovation
this
research
lies
its
comprehensive
consideration
category-level
application
optimization
algorithms
for
replenishment
pricing
strategies.
uniqueness
paper
integrative
approach
to
problem,
providing
refined
models
advanced
methods.
Finally,
thoroughly
describes
steps
design,
including
data
analysis,
cost
markup
construction
an
based
on
intending
offer
supermarkets
plan
adaptable
market
changes.
Energies,
Год журнала:
2024,
Номер
17(17), С. 4436 - 4436
Опубликована: Сен. 4, 2024
Forecasting
the
electricity
market,
even
in
short
term,
is
a
difficult
task,
due
to
nature
of
this
commodity,
lack
storage
capacity,
and
multiplicity
volatility
factors
that
influence
its
price.
The
sensitivity
market
results
appearance
anomalies
during
which
forecasting
models
often
break
down.
aim
paper
present
possibility
using
hybrid
machine
learning
forecast
price
electricity,
especially
when
such
events
occur.
It
includes
automatic
detection
three
different
switch
types
two
independent
models,
one
for
use
periods
stable
markets
other
anomalies.
empirical
tests
conducted
on
data
from
Polish
energy
showed
proposed
solution
improves
overall
quality
prediction
compared
each
model
separately
significantly
anomaly
periods.
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Март 13, 2024
Abstract
A
hybrid
neural
network
based
on
the
attention
mechanism
was
proposed
to
achieve
detection
of
weak
pulse
signals
in
chaotic
noise.
Firstly,
high
sensitivity
small
interference
and
short-term
predictability
,
phase
space
observed
reconstruction.
Then,
Att-CNN-LSTM,
a
predict
signals,
one-step
prediction
error
obtained,
The
problem
signal
can
be
transformed
into
for
error.
Finally,
impulse
detected
from
by
using
Z-test
method.
In
simulation
experiments,
results
model
were
compared
with
those
single
convolutional
(CNN)
long
memory
(LSTM)
model,
least
square
support
vector
machine,
CNN-LSTM
without
mechanism.
show
that
has
higher
accuracy
than
other
models
at
different
signal-to-noise
ratios(SNR),
achieves
good
performance
when
SNR
is
greater
-140.91dB.
Transactions on Economics Business and Management Research,
Год журнала:
2023,
Номер
3, С. 64 - 71
Опубликована: Дек. 25, 2023
This
study
delves
into
the
challenges
and
complexities
of
vegetable
sales
management
in
modern
commercial
environments,
particularly
fresh
food
supermarkets.
By
utilizing
descriptive
statistics
visual
analysis
data,
reveals
correlations
between
different
categories
quantifies
these
using
Pearson's
correlation
coefficient.
Subsequently,
by
integrating
time
series
multi-objective
programming,
a
mathematical
model
is
constructed,
aimed
at
maximizing
profits
under
specific
constraints.
The
innovation
this
research
lies
its
comprehensive
consideration
category-level
application
optimization
algorithms
for
replenishment
pricing
strategies.
uniqueness
paper
integrative
approach
to
problem,
providing
refined
models
advanced
methods.
Finally,
thoroughly
describes
steps
design,
including
data
analysis,
cost
markup
construction
an
based
on
intending
offer
supermarkets
plan
adaptable
market
changes.
