Advances in logistics, operations, and management science book series,
Год журнала:
2024,
Номер
unknown, С. 160 - 198
Опубликована: Апрель 26, 2024
Open
Artificial
Intelligence
(AI)
is
a
research
and
operation
company
that
seeks
to
ensure
persons
around
the
world
can
reap
benefits
of
AI.
Its
focus
on
developing
range
models
have
potential
revolutionize
labour
market
productivity
business
enterprises
across
industries
in
Trinidad
Tobago.
The
use
AI-based
tools
not
only
optimize
every
stage
management
production
process
but
from
perspective
Multi-Factor
Productivity
(MFP)
boost
its
efficiency.
Even
with
such
benefits,
increased
AI
displace
workers,
intensify
educational
skills
mismatch,
stimulate
inequality
between
unskilled
highly
skilled
workers.
This
chapter
examined
impact
MFP
Labor
Dynamics
Tobago,
using
secondary
methodology.
delves
into
connection
MFP,
integration
process,
it
has
dynamics
domestic
industries,
future
work
Global Sustainability Research,
Год журнала:
2024,
Номер
3(1), С. 1 - 24
Опубликована: Янв. 7, 2024
The
aim
of
this
study
was
to
consolidate
current
information
on
the
utilization
Geographic
Information
Systems
(GIS)
and
Remote
Sensing
(RS)
in
agricultural
sector,
with
a
focus
their
role
promoting
evidence-based
policies
practices
enhance
sustainability.
Additionally,
review
sought
identify
challenges
hindering
widespread
adoption
GIS
RS
applications,
particularly
low-
middle-income
nations.
This
employed
methodology
systematic
literature
review.
findings
indicate
that
technology
sector
has
experienced
notable
increase
over
past
few
years.
primary
areas
use
for
have
been
identified
encompass
crop
yield
estimation,
assessment
soil
fertility,
monitoring
cropping
patterns,
evaluation
drought
conditions,
detection
management
pests
diseases,
implementation
precision
agriculture
techniques,
fertilizer
weed
control.
possesses
capacity
augment
sustainability
by
incorporating
spatial
aspect
into
policies.
Furthermore,
potential
facilitating
decision
making
is
expanding.
Given
escalating
peril
climate
change
food
security,
there
exists
heightened
imperative
include
policy
formulation
decision-making
processes
practices.
might
be
beneficial
informing
development
effectively
integrate
sustainable
climate-smart
agriculture.
Natural Resources Conservation and Research,
Год журнала:
2023,
Номер
6(2), С. 3825 - 3825
Опубликована: Дек. 25, 2023
The
recent
progress
in
data
science,
along
with
the
transformation
digital
and
satellite
technology,
has
enhanced
capacity
for
artificial
intelligence
(AI)
applications
forestry
wildlife
domains.
Nevertheless,
swift
proliferation
of
developmental
projects,
agricultural,
urban
areas
pose
a
significant
threat
to
biodiversity
on
global
scale.
Hence,
integration
emerging
technologies
such
as
AI
fields
forests
might
facilitate
efficient
surveillance,
administration,
preservation
forest
resources.
objective
this
paper
is
present
comprehensive
review
how
machine
learning
(ML)
algorithms
are
utilized
sector
conservation
worldwide.
Furthermore,
research
examines
difficulties
encountered
while
implementing
technology
biodiversity.
Enhancing
availability
extensive
pertaining
biodiversity,
utilization
cloud
computing
can
wider
acceptance
implementation
technology.
findings
study
would
inspire
officials,
scientists,
researchers,
conservationists
investigate
potential
purposes
management
conservation.
Journal of Environmental Science and Economics,
Год журнала:
2024,
Номер
3(1), С. 1 - 17
Опубликована: Янв. 1, 2024
Over
the
course
of
previous
three
decades,
Vietnam
has
seen
a
phase
economic
growth,
resulting
in
influx
foreign
direct
investment
(FDI).
However,
it
is
essential
to
note
that
there
was
an
extensive
rise
carbon
dioxide
(CO2)
emissions
throughout
this
period.
The
objective
research
analyze
impact
FDI
and
CO2
on
Vietnam's
utilizing
time
series
data
from
1990
2021.
stationarity
assessed
using
unit
root
tests,
while
autoregressive
distributed
lag
(ARDL)
procedure
utilized
examine
long-
short-run
associations
between
components.
Based
outcomes,
marginal
one
percent
both
associated
with
corresponding
long-term
gain
1.36
1.11
gross
domestic
product
(GDP).
Furthermore,
short
term,
these
increments
yield
increase
0.61
0.29
GDP.
conclusions
study
will
provide
valuable
insights
for
policymakers
crafting
policies
effectively
promote
sustainable
development.
Specifically,
would
aim
strike
balance
capital
growth
derived
investments
expansion,
concurrently
mitigating
emissions.
Abstract
Agriculture
is
one
of
the
major
sources
global
emissions
that
cause
climate
change
while
agricultural
value
added
helps
to
boost
economy
in
developing
countries
like
China.
Therefore,
this
study
aims
investigate
long-
and
short-term
influences
added,
economic
growth
(GDP),
energy
use
on
carbon
dioxide
(CO
2
)
The
autoregressive
distributed
lag
(ARDL)
method
was
used
by
using
annual
time
series
data
from
1990
2021.
empirical
outcomes
revealed
a
1%
increase
would
cut
CO
1.37%
long-run
0.65%
short-run.
However,
found
both
GDP
consumption
have
positive
statistically
significant
effect
emissions.
Furthermore,
an
inverted
U-shaped
association
between
environmental
pollution
discovered
spotting
coefficient
negative
squared,
which
proved
validity
Kuznets
curve
(EKC)
hypothesis.
robustness
ARDL
verified
fully
modified
ordinary
least
squares
(FMOLS),
dynamic
(DOLS),
canonical
cointegration
regression
(CCR)
approaches.
This
offers
comprehensive
set
policy
recommendations
aimed
at
enhancing
These
suggestions
focus
promotion
climate-smart
agriculture,
integration
renewable
production,
adoption
advanced
technologies
within
systems.
Implementing
these
measures
contribute
achievement
China’s
goal
neutrality.
Graphical
SSRN Electronic Journal,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
Artificial
intelligence
(AI)
and
machine
learning
(ML)
are
revolutionizing
renewable
energy
strategies
by
enhancing
efficiency,
reliability,
sustainability.
This
critical
review
examines
the
application
of
AI
ML
techniques
across
various
aspects
energy.
These
models
have
significantly
improved
forecasting,
enabling
precise
predictions
that
optimize
production
distribution.
crucial
in
optimizing
systems,
improving
reducing
costs
through
advanced
analytics
predictive
maintenance.
In
context
smart
grids
management,
support
real-time
decision-making
adaptive
control,
ensuring
optimal
distribution
minimizing
waste.
The
integration
storage
systems
enhances
performance
predicting
requirements
charge-discharge
cycles,
leading
to
more
efficient
use
stored
Moreover,
help
reduce
environmental
impact
processes
lowering
emissions.
also
explores
interplay
between
AI,
Internet
Things
(IoT),
blockchain,
edge
computing
applications.
IoT
devices
enable
data
collection,
which,
when
combined
with
ML,
system
responsiveness
efficiency.
Blockchain
technology
ensures
secure
transparent
transactions,
while
facilitates
faster
processing
at
source,
further
systems.
comprehensive
underscores
transformative
potential
energy,
offering
insights
into
current
advancements
future
perspectives.
It
provides
a
roadmap
for
research
development
this
field.
Deep Underground Science and Engineering,
Год журнала:
2024,
Номер
3(3), С. 286 - 301
Опубликована: Май 23, 2024
Abstract
This
study
delves
into
the
latest
advancements
in
machine
learning
and
deep
applications
geothermal
resource
development,
extending
analysis
up
to
2024.
It
focuses
on
artificial
intelligence's
transformative
role
industry,
analyzing
recent
literature
from
Scopus
Google
Scholar
identify
emerging
trends,
challenges,
future
opportunities.
The
results
reveal
a
marked
increase
intelligence
(AI)
applications,
particularly
reservoir
engineering,
with
significant
observed
post‐2019.
highlights
AI's
potential
enhancing
drilling
exploration,
emphasizing
integration
of
detailed
case
studies
practical
applications.
also
underscores
importance
ongoing
research
tailored
AI
light
rapid
technological
trends
field.
Review of Business and Economics Studies,
Год журнала:
2025,
Номер
12(4), С. 58 - 71
Опубликована: Фев. 11, 2025
This
study
provides
a
theoretical
analysis
of
the
use
and
application
artificial
intelligence
(AI)
in
energy
sector
as
it
relates
to
climate
security.
The
object
is
security
types
economic
activity
social
activity.
subject
research
relation
area
research.
purpose
create
sound
scientific
basis
for
sector,
well
identify
emerging
problems
formation
science-based
approach
policy
development.
authors’
includes
three
interrelated
methodologies:
topic
modeling,
text
mining
part
qualitative
modeling
systematization
results
that
are
adequate
correspond
their
reality;
addition,
authors
supplemented
quantitative
with
heuristic
other
researchers.
concept
parametric
optimization
(PO)
used
an
effective
method
solving
applied
problem
testing
hypothesis
managing
costs
efficiency
based
on
AI
order
achieve
optimal
performance
technical
system
compliance
Sustainable
Development
Goals
(SDGs)
field
study’s
findings
suggest
becoming
fundamental
development
modern
data
complex
relationships
tools
improve
face
sanctions
restrictions.
conclude
truth
has
been
proven:
control
feedback
loop
at
facility
purification
generation
more
cost-effective
technically
alternative
“live”
operator,
which
will
eliminate
human
error
factor.
In
this
regard,
industry,
utilities,
grid
operators
independent
power
producers
must
pay
special
attention
introduction
technologies
into
existing
systems.
