Recently,pharmaceutical
corporations
are
confronting
difficulties
while
tracking
their
products
in
the
supply
chain
process,
allowing
counterfeiters
to
include
fake
medicines
into
market.
Counterfeit
drugs
were
examined
as
a
great
challenge
for
pharmaceutical
sector
worldwide.
Sentiment
analysis
can
be
used
analyse
customer
reviews
of
determine
overall
sentiment
towards
drug.
Positive
indicate
that
drug
is
effective
and
well-tolerated,
negative
may
potential
side
effects
or
lack
effectiveness.
However,
it's
important
note
subfield
natural
language
processing
which
uses
statistical
machine
learning
techniques
identify
extract
subjective
information
from
source
materials.
Therefore,
this
article
introduces
an
Archimedes
Optimization
with
Enhanced
Deep
Learning
based
Recommendation
System
(AOAEDL-RS)
Drug
Supply
Chain
Management.
The
proposed
AOAEDL-RS
technique
majorly
examines
recommendation
drugs.
It
follows
three
stage
process:
preprocessing,
classification,
parameter
tuning.
Firstly,
performs
preprocessing
word2vec
embedding
processes.
Secondly,
context
BiLSTM-CNN
(CBLSTM-CNN)
model
applied
review
classification
classification.
Thirdly,
AOA
optimal
hyperparameter
tuning
CBLSTM-CNN
method.
result
tested
on
dataset
outcomes
show
improved
Kybernetes,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Jan. 12, 2024
Purpose
Nowadays,
in
many
organizations,
products
are
not
delivered
instantly.
So,
the
customers
should
wait
to
receive
their
needed
products,
which
will
form
a
queueing-inventory
model.
Waiting
long
time
queue
may
cause
dissatisfaction
and
churn
of
loyal
customers,
can
be
significant
loss
for
organizations.
Although
studies
have
been
done
on
models,
more
practical
models
this
area
needed,
such
as
considering
customer
prioritization.
Moreover,
minimizing
total
cost
organization
has
overlooked.
Design/methodology/approach
This
paper
compare
several
machine
learning
(ML)
algorithms
prioritize
customers.
benefiting
from
best
ML
algorithm,
categorized
into
different
classes
based
value
importance.
Finally,
mathematical
model
developed
determine
allocation
policy
on-hand
each
group
through
multi-channel
service
retailing
minimize
organization’s
costs
increase
customers'
satisfaction
level.
Findings
To
investigate
application
proposed
method,
real-life
case
study
vaccine
distribution
at
Imam
Khomeini
Hospital
Tehran
addressed
ensure
validation.
The
model’s
accuracy
was
assessed
excellent
results
generated
by
algorithms,
problem
modeling
study.
Originality/value
Prioritizing
with
help
optimizing
waiting
queues
reduce
could
lead
an
levels
among
prevent
churn.
study’s
uniqueness
lies
its
focus
determining
queue,
is
relatively
rare
topic
research
queueing
management
systems.
Additionally,
obtained
provide
strong
validation
functionality.
Journal of Innovation & Knowledge,
Journal Year:
2024,
Volume and Issue:
9(1), P. 100468 - 100468
Published: Jan. 1, 2024
The
development
of
urban
digital
platforms
has
changed
its
entrepreneurial
environment
and
affected
regional
innovation
vitality.
We
calculated
the
index
294
prefecture-level
cities
in
China
between
2013
2020
using
principal
component
analysis
method.
used
microdata
enterprise
registration
information
to
describe
activity.
Digital
have
promoted
activity
significantly.
Moreover,
alleviating
labour
market
distortions,
optimizing
financial
environment,
improving
technological
are
virtual
channels
for
increase
Furthermore,
play
a
more
significant
role
promoting
eastern
region
with
better
industrial
structures.
This
impact
nonlinear
increasing
"marginal
effect"
which
faster
platforms,
effect
on
Sustainability,
Journal Year:
2023,
Volume and Issue:
15(8), P. 6905 - 6905
Published: April 19, 2023
The
fierce
competition
in
international
markets
and
the
rapid
advancements
information
technology
result
shorter
lead
times,
lower
transportation
capacity,
higher
demand.
supply
chain
network
is
one
of
most
crucial
areas
concentration
majority
business
circumstances.
Blockchain
a
promising
option
for
safe
exchange
network.
Although
preserving
security
at
every
level
blockchain
somewhat
important,
cryptographic
methodologies
are
frequently
used
existing
works.
novel
perceptive
craving
game
search
(PCGS)
optimization
algorithm
to
optimally
generate
key
data
sanitization,
which
assures
privacy
logistics
data.
Here,
original
obtained
from
manufacturer
sanitized
with
an
optimal
generated
by
using
PCGS
algorithm,
avoiding
risk
unauthorized
access
swarm
that
causes
system
lag.
Moreover,
transmitted
allowed
parties
via
different
sub-chains.
same
on
receiving
customer
side
reconstructing
performance
results
proposed
blockchain-based
preservation
model
validated
various
parameters.
Recently,pharmaceutical
corporations
are
confronting
difficulties
while
tracking
their
products
in
the
supply
chain
process,
allowing
counterfeiters
to
include
fake
medicines
into
market.
Counterfeit
drugs
were
examined
as
a
great
challenge
for
pharmaceutical
sector
worldwide.
Sentiment
analysis
can
be
used
analyse
customer
reviews
of
determine
overall
sentiment
towards
drug.
Positive
indicate
that
drug
is
effective
and
well-tolerated,
negative
may
potential
side
effects
or
lack
effectiveness.
However,
it's
important
note
subfield
natural
language
processing
which
uses
statistical
machine
learning
techniques
identify
extract
subjective
information
from
source
materials.
Therefore,
this
article
introduces
an
Archimedes
Optimization
with
Enhanced
Deep
Learning
based
Recommendation
System
(AOAEDL-RS)
Drug
Supply
Chain
Management.
The
proposed
AOAEDL-RS
technique
majorly
examines
recommendation
drugs.
It
follows
three
stage
process:
preprocessing,
classification,
parameter
tuning.
Firstly,
performs
preprocessing
word2vec
embedding
processes.
Secondly,
context
BiLSTM-CNN
(CBLSTM-CNN)
model
applied
review
classification
classification.
Thirdly,
AOA
optimal
hyperparameter
tuning
CBLSTM-CNN
method.
result
tested
on
dataset
outcomes
show
improved
