Ecotoxicology and Environmental Safety,
Journal Year:
2023,
Volume and Issue:
257, P. 114911 - 114911
Published: April 15, 2023
Machine
learning
(ML)
is
an
advanced
computer
algorithm
that
simulates
the
human
process
to
solve
problems.
With
explosion
of
monitoring
data
and
increasing
demand
for
fast
accurate
prediction,
ML
models
have
been
rapidly
developed
applied
in
air
pollution
research.
In
order
explore
status
applications
research,
a
bibliometric
analysis
was
made
based
on
2962
articles
published
from
1990
2021.
The
number
publications
increased
sharply
after
2017,
comprising
approximately
75%
total.
Institutions
China
United
States
contributed
half
all
with
most
research
being
conducted
by
individual
groups
rather
than
global
collaborations.
Cluster
revealed
four
main
topics
application
ML:
chemical
characterization
pollutants,
short-term
forecasting,
detection
improvement
optimizing
emission
control.
rapid
development
algorithms
has
capability
characteristics
multiple
analyze
reactions
their
driving
factors,
simulate
scenarios.
Combined
multi-field
data,
are
powerful
tool
analyzing
atmospheric
processes
evaluating
management
quality
deserve
greater
attention
future.
Energy Strategy Reviews,
Journal Year:
2022,
Volume and Issue:
45, P. 101017 - 101017
Published: Dec. 13, 2022
Economic
development
and
the
comfort-loving
nature
of
human
beings
in
recent
years
have
resulted
increased
energy
demand.
Since
resources
are
scarce
should
be
preserved
for
future
generations,
optimizing
systems
is
ideal.
Still,
due
to
complexity
integrated
systems,
such
a
feat
by
no
means
easy.
Here
where
computer-aided
decision-making
can
very
game-changing
determining
optimum
point
supply
The
concept
artificial
intelligence
(AI)
machine
learning
(ML)
was
born
twentieth
century
enable
computers
simulate
humans'
capabilities.
then,
data
mining
become
increasingly
essential
areas
many
different
research
fields.
Naturally,
section
one
area
beneficial.
This
paper
uses
VOSviewer
software
investigate
review
usage
field
proposes
promising
yet
neglected
or
unexplored
which
these
concepts
used.
To
achieve
this,
2000
most
papers
addition
cited
ones
energy-related
keywords
were
studied
their
relationship
AI-
ML-related
visualized.
results
revealed
trends
from
basic
more
cutting-edge
topics
that
explored.
Results
also
showed
commercial
aspect,
patents
submitted
had
sharp
increase.
Energies,
Journal Year:
2022,
Volume and Issue:
15(10), P. 3834 - 3834
Published: May 23, 2022
In
recent
decades,
climate
change
and
a
shortage
of
resources
have
brought
about
the
need
for
technology
in
agriculture.
Farmers
been
forced
to
use
information
innovation
communication
order
enhance
production
efficiency
crop
resilience.
Systems
engineering
infrastructure
based
on
Internet
Things
(IoT)
are
main
novel
approaches
that
generated
growing
interest.
agriculture,
IoT
solutions
according
challenges
Industry
4.0
can
be
applied
greenhouses.
Greenhouses
protected
environments
which
best
plant
growth
achieved.
smart
greenhouses
relates
sensors,
devices,
real-time
monitoring
data
collection
processing,
efficiently
control
indoor
parameters
such
as
exposure
light,
ventilation,
humidity,
temperature,
carbon
dioxide
level.
This
paper
presents
current
state
art
IoT-based
applications
greenhouses,
underlining
benefits
opportunities
this
agriculture
environment.
International Journal of Energy Economics and Policy,
Journal Year:
2024,
Volume and Issue:
14(1), P. 172 - 183
Published: Jan. 15, 2024
The
research
landscape
on
the
applications
of
advanced
computational
tools
(ACTs)
such
as
machine/deep
learning
and
neural
network
algorithms
for
energy
power
generation
(EPG)
was
critically
examined
through
publication
trends
bibliometrics
data
analysis.
Elsevier
Scopus
database
PRISMA
methodology
were
employed
to
identify
screen
published
documents,
whereas
bibliometric
analysis
software
VOSviewer
used
analyse
co-authorships,
citations,
keyword
occurrences.
results
showed
that
152
documents
have
been
topic
comprising
conference
proceedings
(58.6%)
articles
(41.4%)
between
2004
2022.
Publication
revealed
number
publications
increased
from
1
31
or
by
3,000%
over
same
period,
which
ascribed
growing
scientific
interest
impact
topic.
Stakeholder
top
authors/researchers
are
Anvari
M,
Ghaderi
SF
Saberi
most
prolific
affiliation
nations
actively
engaged
in
North
China
Electric
Power
University,
China,
respectively.
Conversely,
funding
agency
backing
is
National
Natural
Science
Foundation
(NSFC).
Co-authorship
high
levels
collaboration
researching
compared
authors
affiliations.
Hotspot
three
major
thematic
focus
areas
namely;
Energy
Grid
Forecasting,
Generation
Control,
Intelligent
Optimization.
In
conclusion,
study
application
ACTs
EPG
an
active,
multidisciplinary,
area
with
potential
more
impactful
contributions
society
at
large.
Environmental Science and Pollution Research,
Journal Year:
2024,
Volume and Issue:
31(39), P. 52448 - 52472
Published: Aug. 16, 2024
In
this
paper,
it
is
aimed,
for
the
first
time,
at
deriving
simple
models,
leveraging
trend
analysis
in
order
to
estimate
future
greenhouse
gas
emissions
associated
with
coal
combustion.
Due
expectations
of
becoming
center
global
economic
development
future,
BRICS-T
(Brazil,
Russian
Federation,
India,
China,
South
Africa,
and
Turkiye)
countries
are
adopted
as
cases
study.
Following
models'
derivation,
their
statistical
validations
estimating
accuracies
also
tested
through
various
metrics.
addition,
combustion
estimated
by
derived
models.
The
results
demonstrate
that
models
can
be
successfully
used
a
tool
combustions
accuracy
ranges
from
least
90%
almost
98%.
Moreover,
show
total
amount
relevant
world
will
increase
14
BtCO
