With
the
continuous
advancement
of
digital
transformation,
payments
are
playing
an
increasingly
important
role
in
financial
industry.
This
study
aims
to
utilize
machine
learning
models
predict
and
analyze
payment
behavior.
Initially,
background
significance
sector
introduced.
Subsequently,
current
status
trends
traditional
distribution
reviewed,
alongside
related
work
on
behavior
prediction.
Methodologically,
principles
applications
such
as
logistic
regression,
decision
trees,
random
forests
elaborated,
along
with
experimental
design
data
preprocessing
methods.
The
results
discussion
section
illustrates
performance
each
model
prediction
explores
their
impact
credit
decisions.
exploration
equips
institutions
more
effective
user
analysis
risk
management
tools,
thereby
fostering
future
development
application
technologies.
Academic Journal of Science and Technology,
Journal Year:
2024,
Volume and Issue:
10(1), P. 74 - 80
Published: March 26, 2024
This
research
explores
the
intersection
of
artificial
intelligence
and
finance,
focusing
on
emergence
intelligent
investment
advisers,
commonly
known
as
Robo-advisers
(RAs).
These
RAs
utilize
robust
computer
models
algorithms
to
deliver
personalized
asset
management
plans
for
users.
Notably,
Wealthfront
is
highlighted
a
prominent
platform
in
this
field,
offering
automated
services
aimed
at
optimizing
returns.
The
study
investigates
impact
users'
past
performance
their
adoption
considering
factors
such
previous
defaults
recent
performance.
It
reveals
that
frequent
adjustments
use
advisers
may
hinder
long-term
objectives,
emphasizing
importance
consistent
usage
fully
capitalize
benefits.
Furthermore,
emphasizes
significance
transparency,
user-friendly
interaction
design,
tailored
financial
foster
user
trust
enhance
optimization
advisers'
design.
Academic Journal of Science and Technology,
Journal Year:
2024,
Volume and Issue:
10(1), P. 62 - 68
Published: March 26, 2024
Natural
Language
Processing
(NLP)
is
an
interdisciplinary
field
of
computer
science,
artificial
intelligence,
and
linguistics
that
focuses
on
the
ability
computers
to
understand,
process,
generate,
simulate
human
language
in
order
achieve
have
natural
conversations
with
humans.
The
underlying
principles
processing
are
at
multiple
levels,
including
linguistics,
statistics.
It
involves
study
structure,
semantics,
grammar
pragmatics,
as
well
statistical
analysis
modeling
large-scale
corpora.
In
process
concrete
implementation,
it
necessary
levels.
Based
this,
this
paper
combined
deep
learning
technology
conduct
sentiment
patients'
comments,
so
recommend
drugs
more
suitable
for
patients,
thus
achieving
accurate
drug
prescribing
personalized
recommendation.
Engineering Applications of Computational Fluid Mechanics,
Journal Year:
2024,
Volume and Issue:
18(1)
Published: Feb. 29, 2024
Energy-related
CO2
emissions
are
one
of
the
biggest
concerns
facing
urban
design
today,
increasing
rapidly
as
cities
grow.
This
study
uses
inputs
GDP
G8
nations
(from
1990
to
2016)
depending
on
utilization
various
energy
sources,
including
coal,
oil,
natural
gas,
and
renewable
energy.
Multilayer
perceptrons
(MLP)
combined
with
nature-inspired
optimization
algorithms,
such
Heap-Based
Optimizer
(HBO),
Teaching-Learning-Based
Optimization
(TLBO),
Whale
Algorithm
(WOA),
Vortex
Search
algorithm
(VS),
Earthworm
(EWA),
create
a
dependable
predictive
network
that
takes
complexity
problem
into
account.
Our
key
contributions
lie
in
developing
comprehensively
evaluating
these
hybrid
models
assessing
their
efficacy
capturing
intricate
dynamics
carbon
emissions.
The
found
TLBO
VS
outperform
other
algorithms
emission
computation
accuracy.
has
higher
training
MSE
(3.6778)
lower
testing
(4.4673),
suggesting
larger
squared
errors
data
MSE,
less
overfitting
due
better
generalization
set.
Academic Journal of Science and Technology,
Journal Year:
2024,
Volume and Issue:
10(1), P. 50 - 55
Published: March 26, 2024
Human
behavior
recognition
refers
to
the
classification
task
of
identifying
specific
actions
human
characters
based
on
characteristics
body
and
completed
through
a
algorithm.
It
has
wide
range
applications
in
intelligent
surveillance,
video
retrieval
so
on.
The
main
challenge
this
direction
is
accurately
extract
semantic
information
each
describe
its
dynamic
changes
space
time.
Therefore,
article
introduces
latest
research
progress
field
recognition.
Through
deep
learning
techniques,
particularly
convolutional
neural
networks
recurrent
networks,
movements
data
can
be
effectively
identified.
However,
models
lack
interpretability,
which
practical
applications.
researchers
also
introduce
application
traditional
methods
learning-based
recognition,
explore
advantages
processing
multi-time
scale
introducing
attention
mechanisms.
Finally,
paper
summarizes
potential
technology
combined
with
multimodal
behavioral
analysis,
provides
prospects
for
smart
fitness,
health
care
other
fields.
Artificial Intelligence Review,
Journal Year:
2024,
Volume and Issue:
57(8)
Published: July 2, 2024
Abstract
Network
selection
in
heterogeneous
wireless
networks
(HWNs)
is
a
complex
issue
that
requires
thorough
understanding
of
service
features
and
user
preferences.
This
because
the
various
access
technologies
have
varying
capabilities
limitations,
best
network
for
voice,
video,
data
depends
on
variety
factors.
For
selecting
optimal
HWNs,
factors
such
as
user’s
position,
accessible
resources,
quality
requirements,
preferences
must
be
considered.
The
classical
decision
making
procedure
very
difficult
uncertain
to
select
desirable
HWNs
data.
Therefore,
we
develop
novel
model
based
feed-forward
neural
under
double
hierarchy
linguistic
information
In
this
article,
introduce
using
Hamacher
t-norm
t-conorm.
Further,
applies
model,
first
take
given
about
use
converting
function
convert
into
term
set.
We
calculate
hidden
layer
output
by
aggregation
operations.
Finally,
sigmoid
activation
decide
according
ranking.
proposed
approach
compared
with
other
existing
models
results
comparison
show
technique
applicable
reliable
support
model.
Journal of Theory and Practice of Engineering Science,
Journal Year:
2024,
Volume and Issue:
4(03), P. 176 - 182
Published: March 25, 2024
As
large
language
models
gain
traction
in
the
financial
sector,
they
are
revolutionizing
workflows
of
professionals.
From
data
analysis
and
market
forecasting
to
risk
assessment
customer
management,
these
demonstrate
significant
potential
value.
By
automating
processing
tasks,
enhance
productivity
empower
professionals
derive
deeper
insights
make
more
precise
decisions.
This
article
explores
application
conversational
intelligent
reporting
systems,
leveraging
artificial
intelligence
models,
within
industry.
It
examines
how
systems
streamline
processes,
facilitate
efficient
communication,
contribute
informed
decision-making,
ultimately
reshaping
landscape
operations.
