Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
Case Studies in Thermal Engineering,
Год журнала:
2024,
Номер
60, С. 104743 - 104743
Опубликована: Июнь 24, 2024
In
this
study,
eXtreme
Gradient
Boosting
(XGBoost)
and
Light
(LightGBM)
algorithms
were
used
to
model-predict
the
drying
characteristics
of
banana
slices
with
an
indirect
solar
drier.
The
relationships
between
independent
variables
(temperature,
moisture,
product
type,
water
flow
rate,
mass
product)
dependent
(energy
consumption
size
reduction)
established.
For
energy
consumption,
XGBoost
demonstrates
superior
performance
R2
0.9957
during
training
0.9971
testing,
alongside
minimal
MSE
0.0034
0.0008
testing
phase
indicating
high
predictive
accuracy
low
error
rates.
Conversely,
LGBM
shows
lower
values
(0.9061
training,
0.8809
testing)
higher
0.0747
0.0337
reflecting
poorer
performance.
Similarly,
for
shrinkage
prediction,
outperforms
LGBM,
evidenced
by
(0.9887
0.9975
(0.2527
0.4878
testing).
comparative
statistics
showed
that
regularly
outperformed
LightGBM.
game
theory-based
Shapley
functions
revealed
temperature
types
most
influential
features
model.
These
findings
illustrate
practical
applicability
LightGBM
models
in
food
operations
towards
optimizing
conditions,
improving
quality,
reducing
consumption.
Язык: Английский
Application of Artificial Intelligence and Machine Learning in Assessing Solar Energy Potential
Опубликована: Март 21, 2025
Язык: Английский
Fueling the future: Exploring the synergy of artificial intelligence-based algorithms and the use of biofuels in engine development
Journal of the Taiwan Institute of Chemical Engineers,
Год журнала:
2024,
Номер
unknown, С. 105729 - 105729
Опубликована: Сен. 1, 2024
Язык: Английский
Improving syngas yield and quality from biomass/coal co-gasification using cooperative game theory and local interpretable model-agnostic explanations
International Journal of Hydrogen Energy,
Год журнала:
2024,
Номер
96, С. 892 - 907
Опубликована: Ноя. 29, 2024
Язык: Английский
Strategic Roadmap for Adopting Data-Driven Proactive Measures in Solar Logistics
Applied Sciences,
Год журнала:
2024,
Номер
14(10), С. 4246 - 4246
Опубликована: Май 16, 2024
This
study
presents
a
comprehensive
overview
of
the
solar
industry’s
transition
towards
resilient
energy
solutions,
emphasizing
critical
role
data-driven
practices
in
driving
this
through
responsible
resource
management.
As
continuous
technological
refinement
is
essential
to
optimize
energy’s
potential,
smart
use
available
data
plays
significant
part
enhancing
accessibility
panels.
Building
upon
prior
research
investigating
influence
Big
Data
on
logistics,
paper
proposes
hybrid
Multi-Criteria
Decision-Making
(MCDM)
methodology
based
expert
experience,
providing
practical
support
implementation
proactive
measures
within
industry.
Specifically,
focuses
aimed
at
effectively
implementing
two
main
logistic
strategies,
which
are
Route
Optimization
(RO)
and
Warehouse
Management
(WM).
A
rigorous
analysis
criteria
considered
be
relevant
literature
first
conducted.
Criteria
will
screened
weighted
eventually
act
as
drivers
toward
measure
assessment
prioritization.
final
sensitivity
culminates
formalization
findings
formulation
pragmatic
roadmap
tailored
for
industry
practitioners,
designed
increase
operational
efficiency
while
integrating
key
sustainability
principles
across
supply
chain
endeavors.
Язык: Английский
Using hydrogen as potential fuel for internal combustion engines: A comprehensive assessment
D. Huynh,
Thanh Hai Nguyen,
Duc Chuan Nguyen
и другие.
International Journal of Renewable Energy Development,
Год журнала:
2024,
Номер
14(1), С. 83 - 103
Опубликована: Янв. 1, 2024
This
comprehensive
review
explores
the
feasibility
and
potential
of
using
hydrogen
gas
as
a
fuel
for
internal
combustion
engines,
topic
growing
importance
in
context
global
efforts
to
reduce
greenhouse
emissions
transition
towards
sustainable
energy
sources.
Hydrogen,
known
its
high
content
clean
properties,
presents
promising
alternative
traditional
fossil
fuels.
paper
examines
chemical
properties
benefits
over
conventional
fuels,
particularly
focusing
on
technological
advancements
modifications
required
compression
ignition
spark
engines
efficiently
utilize
hydrogen.
The
delves
into
necessary
engine
design
modification,
injection
systems,
characteristics,
emission
control
technologies
specific
both
engines.
Furthermore,
it
addresses
environmental
impacts,
including
reductions
gases
other
pollutants,
evaluates
economic
implications,
such
production
costs
compared
solutions.
Key
challenges
associated
with
storage,
distribution,
safety
are
discussed,
along
solutions
innovations
currently
under
investigation.
aims
provide
thorough
understanding
current
state
guiding
future
research
development
this
vital
field.
Язык: Английский