Journal of Organizational and End User Computing,
Journal Year:
2025,
Volume and Issue:
37(1), P. 1 - 33
Published: Feb. 13, 2025
In
response
to
the
challenges
posed
by
globalization
and
rapid
technological
advancements,
traditional
static
pricing
models
are
no
longer
sufficient
capture
dynamic
nature
of
consumer
behavior
market
fluctuations.
This
study
proposes
a
“Multi-dimensional
Dynamic
Pricing
Optimization
Consumer
Behavior
Prediction
Model
Driven
Big
Data,”
which
integrates
multi-source
data
reinforcement
learning
improve
strategies.
Through
hybrid
model
architecture
using
Random
Forest
LSTM,
it
captures
both
time-series
features.
Experimental
results
show
that
proposed
significantly
outperforms
baseline
models,
achieving
43%
reduction
in
Mean
Squared
Error
(MSE),
28%
decrease
Absolute
Percentage
(MAPE),
6.5%
increase
Accuracy,
14.7%
Cumulative
Revenue.
These
findings
confirm
model's
ability
enhance
prediction
accuracy,
optimize
strategies,
maximize
revenue,
demonstrating
its
potential
for
real-world
applications
industries
like
e-commerce,
finance,
advertising.
Energies,
Journal Year:
2024,
Volume and Issue:
17(16), P. 4128 - 4128
Published: Aug. 19, 2024
The
integration
of
renewable
energy
sources
(RES)
into
smart
grids
has
been
considered
crucial
for
advancing
towards
a
sustainable
and
resilient
infrastructure.
Their
is
vital
achieving
sustainability
among
all
clean
sources,
including
wind,
solar,
hydropower.
This
review
paper
provides
thoughtful
analysis
the
current
status
grid,
focusing
on
integrating
various
RES,
such
as
wind
grid.
highlights
significant
role
RES
in
reducing
greenhouse
gas
emissions
traditional
fossil
fuel
reliability,
thereby
contributing
to
environmental
empowering
security.
Moreover,
key
advancements
grid
technologies,
Advanced
Metering
Infrastructure
(AMI),
Distributed
Control
Systems
(DCS),
Supervisory
Data
Acquisition
(SCADA)
systems,
are
explored
clarify
related
topics
usage
technologies
enhances
efficiency,
resilience
introduced.
also
investigates
application
Machine
Learning
(ML)
techniques
management
optimization
within
with
techniques.
findings
emphasize
transformative
impact
advanced
alongside
need
continued
innovation
supportive
policy
frameworks
achieve
future.
Artificial Intelligence Review,
Journal Year:
2024,
Volume and Issue:
57(4)
Published: March 12, 2024
Abstract
Environmental
sustainability
is
a
worldwide
key
challenge
attracting
increasing
attention
due
to
climate
change,
pollution,
and
biodiversity
decline.
Reinforcement
learning,
initially
employed
in
gaming
contexts,
has
been
recently
applied
real-world
domains,
including
the
environmental
realm,
where
uncertainty
challenges
strategy
learning
adaptation.
In
this
work,
we
survey
literature
identify
main
applications
of
reinforcement
predominant
methods
address
these
challenges.
We
analyzed
181
papers
answered
seven
research
questions,
e.g.,
“How
many
academic
studies
have
published
from
2003
2023
about
RL
for
sustainability?”
“What
were
application
domains
methodologies
used?”.
Our
analysis
reveals
an
exponential
growth
field
over
past
two
decades,
with
rate
0.42
number
publications
(from
2
2007
53
2022),
strong
interest
issues
related
energy
fields,
preference
single-agent
approaches
deal
sustainability.
Finally,
work
provides
practitioners
clear
overview
open
problems
that
should
be
tackled
future
research.
Medical Sciences,
Journal Year:
2025,
Volume and Issue:
13(1), P. 8 - 8
Published: Jan. 11, 2025
Depression
poses
significant
challenges
to
global
healthcare
systems
and
impacts
the
quality
of
life
individuals
their
family
members.
Recent
advancements
in
artificial
intelligence
(AI)
have
had
a
transformative
impact
on
diagnosis
treatment
depression.
These
innovations
potential
significantly
enhance
clinical
decision-making
processes
improve
patient
outcomes
settings.
AI-powered
tools
can
analyze
extensive
data—including
medical
records,
genetic
information,
behavioral
patterns—to
identify
early
warning
signs
depression,
thereby
enhancing
diagnostic
accuracy.
By
recognizing
subtle
indicators
that
traditional
assessments
may
overlook,
these
enable
providers
make
timely
precise
decisions
are
crucial
preventing
onset
or
escalation
depressive
episodes.
In
terms
treatment,
AI
algorithms
assist
personalizing
therapeutic
interventions
by
predicting
effectiveness
various
approaches
for
individual
patients
based
unique
characteristics
history.
This
includes
recommending
tailored
plans
consider
patient’s
specific
symptoms.
Such
personalized
strategies
aim
optimize
overall
efficiency
healthcare.
theoretical
review
uniquely
synthesizes
current
evidence
applications
primary
care
depression
management,
offering
comprehensive
analysis
both
personalization
capabilities.
Alongside
advancements,
we
also
address
conflicting
findings
field
presence
biases
necessitate
important
limitations.
Diagnostics,
Journal Year:
2025,
Volume and Issue:
15(6), P. 787 - 787
Published: March 20, 2025
The
increasing
prevalence
of
cardiovascular
complications
in
cancer
patients
due
to
cardiotoxic
treatments
has
necessitated
advanced
monitoring
and
predictive
solutions.
Cardio-oncology
is
an
evolving
interdisciplinary
field
that
addresses
these
challenges
by
integrating
artificial
intelligence
(AI)
smart
cardiac
devices.
This
comprehensive
review
explores
the
integration
devices
cardio-oncology,
highlighting
their
role
improving
risk
assessment
early
detection
real-time
cardiotoxicity.
AI-driven
techniques,
including
machine
learning
(ML)
deep
(DL),
enhance
stratification,
optimize
treatment
decisions,
support
personalized
care
for
oncology
at
risk.
Wearable
ECG
patches,
biosensors,
AI-integrated
implantable
enable
continuous
surveillance
analytics.
While
advancements
offer
significant
potential,
such
as
data
standardization,
regulatory
approvals,
equitable
access
must
be
addressed.
Further
research,
clinical
validation,
multidisciplinary
collaboration
are
essential
fully
integrate
solutions
into
cardio-oncology
practices
improve
patient
outcomes.
Internet of Things,
Journal Year:
2023,
Volume and Issue:
24, P. 100978 - 100978
Published: Nov. 1, 2023
The
advent
of
the
Internet
Things
(IoT)
has
resulted
in
significant
technical
development
healthcare
sector,
enabling
establishment
Medical
Cyber-Physical
Systems
(MCPS).
increased
number
MCPS
generates
a
massive
amount
privacy-sensitive
data,
hence
it
is
important
to
enhance
security
devices
and
data
transmission
MCPS.
Earlier
several
research
studies
were
undertaken
order
healthcare,
but
none
them
could
adapt
changing
behaviors
attacks.
Here
role
blockchain
Reinforcement
Learning
(RL)
comes
into
play
since
can
adjust
itself
nature
attacks,
thus
preventing
any
kind
This
work
proposes
solution,
named
Cogni-Sec,
which
employs
decentralized
cognitive
architecture
addresses
issue.
Blockchain
incorporated
approach
for
storage
increase
degree
modules.
Hyperledger
Fabric
applied
as
base
shows
transaction
query
results
with
nearly
10%
throughput,
69%
less
memory
consumption,
15%
lower
CPU
usage
when
compared
Ethereum.
Further
risk
at
block
mining
level
within
network
reduced
by
introducing
distributed
replacement
miner
nodes,
imitates
behavior
miners
environment.
Different
multi-agent
learning
systems
have
been
evaluated
building
agent.
Among
these,
a3c
agent
setup
yields
optimum
cumulative
reward
median
value
54.5
minimizes
maximum
threats.
AI,
Journal Year:
2023,
Volume and Issue:
5(1), P. 38 - 54
Published: Dec. 20, 2023
In
recent
years,
artificial
intelligence
(AI)
has
seen
remarkable
advancements,
stretching
the
limits
of
what
is
possible
and
opening
up
new
frontiers.
This
comparative
review
investigates
evolving
landscape
AI
providing
a
thorough
exploration
innovative
techniques
that
have
shaped
field.
Beginning
with
fundamentals
AI,
including
traditional
machine
learning
transition
to
data-driven
approaches,
narrative
progresses
through
core
such
as
reinforcement
learning,
generative
adversarial
networks,
transfer
neuroevolution.
The
significance
explainable
(XAI)
emphasized
in
this
review,
which
also
explores
intersection
quantum
computing
AI.
delves
into
potential
transformative
effects
technologies
on
advancements
highlights
challenges
associated
their
integration.
Ethical
considerations
discussions
bias,
fairness,
transparency,
regulatory
frameworks,
are
addressed.
aims
contribute
deeper
understanding
rapidly
field
Reinforcement
lead
research,
growing
emphasis
transparency.
Neuroevolution
though
less
studied,
show
for
future
developments.
Buildings,
Journal Year:
2024,
Volume and Issue:
14(11), P. 3480 - 3480
Published: Oct. 31, 2024
This
paper
explores
the
transformative
impact
of
agent-based
modeling
(ABM)
on
architecture,
engineering,
and
construction
(AEC)
industry,
highlighting
its
indispensable
role
in
revolutionizing
project
management,
processes,
safety
protocols,
sustainability
initiatives
including
energy
optimization
occupants’
comfort.
Through
an
in-depth
review
178
documents
published
between
1970
2024
current
practices
integration
ABM
with
emerging
digital
technologies,
this
study
underscores
critical
importance
facilitating
enhanced
decision-making,
resource
optimization,
complex
system
simulations.
For
instance,
is
shown
to
reduce
delays
by
up
15%
through
allocation
improve
outcomes
simulating
worker
behavior
identifying
potential
hazards
dynamic
environments.
The
results
reveal
ABM’s
significantly
methodologies,
integrate
technological
advancements
seamlessly,
contribute
development
sustainable
resilient
building
practices.
Furthermore,
identifies
key
areas
for
future
research,
exploration
capabilities
conjunction
other
innovations
unlock
new
avenues
efficiency
construction.
sets
out
a
forward-looking
agenda
providing
approach
address
contemporary
challenges
harness
opportunities
innovation
growth
AEC
sector.
International Journal of Religion,
Journal Year:
2024,
Volume and Issue:
5(10), P. 4766 - 4782
Published: July 26, 2024
Artificial
intelligence
(AI)
is
a
powerful
technology
that
helps
cybersecurity
teams
automate
repetitive
tasks,
accelerate
threat
detection
and
response,
improve
the
accuracy
of
their
actions
to
strengthen
security
posture
against
various
issues
cyberattacks.
This
objective
focuses
on
analysing
how
AI-based
cyber
(CS)
solutions
performance
in
financial
transactions
banking
sectors.
It
also
aims
identify
latest
advancements
AI-driven
CS)
research
enhance
operational
efficiency
sector.
article
presents
systematic
literature
review
detailed
analysis
AI
use
cases
for
transactions.
The
resulted
800
studies,
which
225
articles
remain.
paper
will
provide
readers
with
comprehensive
overview
potential
identifies
future
opportunities
examining
application
areas,
advanced
methods,
data
representation,
development
new
infrastructures
successful
adoption
might
increase
systems’
by
increasing
defence
approaches
machine
learning
deep
learning,
fraud
detection,
this
makes
sure
secure
safe
transaction.
study
make
safer
security.
highlights
vital
role
evaluation
continuous
adaptation
AI.
In
near
future,
topic
should
focus
more
collaboration
among
AI,
security,
system
developers
better
secured
outcomes.
