Precision Agriculture Optimization based on Multi-Armed Bandits Algorithm: Wheat Yield Optimization under Different Temperature and Precipitation Conditions
Qikang Huang
No information about this author
ITM Web of Conferences,
Journal Year:
2025,
Volume and Issue:
73, P. 01013 - 01013
Published: Jan. 1, 2025
Climate
change
and
the
growing
unpredictability
of
environmental
elements
such
as
temperature
precipitation
present
considerable
challenges
to
contemporary
agriculture.
Data-driven
algorithms
promising
solutions
by
offering
more
precise
tools
for
optimizing
crop
yields
resource
efficiency
tackle
these
challenges.
Among
approaches,
multi-armed
bandit
(MAB)
algorithm
effectively
balances
exploration
exploitation,
showcasing
potential
agricultural
decision-making.
This
study
investigates
four
widely
utilized
Multi-Armed
Bandits
algorithms:
Explore
Then
Commit
(ETC),
Upper
Confidence
Bound
(UCB),
Asymptotically
Optimal
UCB,
Thompson
Sampling
(TS).
The
objective
is
optimize
wheat
yield
under
varying
conditions
while
also
assessing
effectiveness
different
in
achieving
this
goal.
experiment
demonstrates
that
UCB
optimal
analyzing
data
on
total
during
growth
wheat.
.
Furthermore,
TS
significantly
outperforms
others
flat
throughout
period.
Therefore,
can
identify
most
suitable
rainfall
a
changing
environment.
In
contrast,
determine
requirements
similar
fluctuations.
These
insights
assist
practitioners
timely
adjusting
their
strategies
enhance
yield.
Additionally,
it
provides
model
those
who
want
use
MAB
improve
yields.
Language: Английский
Stage Segmentation of Rural Transformation and Comparisons Among Bangladesh, China, Indonesia, and Pakistan: Combining Machine Learning and New Structural Economics to Facilitate International Agricultural Development and Policy Design
Asia & the Pacific Policy Studies,
Journal Year:
2025,
Volume and Issue:
12(2)
Published: Feb. 27, 2025
ABSTRACT
This
paper
contributes
a
new
paradigm
for
international
agricultural
development
research.
It
uses
machine
learning
techniques
to
aid
expert
diagnosis
of
problems
in
conjunction
with
New
Structural
Economics
(NSE)
analyse
and
design
policies
enable
effective
rural
transformation.
conducts
multi‐country,
multi‐regional,
multi‐level
multi‐dimensional
analysis
Bangladesh,
China,
Indonesia,
Pakistan
identify
stage
segmentations
transformation
examine
stagewise
associate
applicable
learnings
across
each
dimension.
By
presenting
structured
stages
transformation,
we
provide
guidance
on
designing
dynamic
comparative‐advantage‐adapting
that
are
able
adapt
at
stage.
analytical
procedure
can
serve
other
relevant
studies.
Language: Английский
Artificial intelligence in agriculture: applications, approaches, and adversities across pre-harvesting, harvesting, and post-harvesting phases
Iran Journal of Computer Science,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 14, 2025
Language: Английский
Living Lab for the Diffusion of Enabling Technologies in Agriculture: The Case of Sicily in the Mediterranean Context
Agriculture,
Journal Year:
2024,
Volume and Issue:
14(12), P. 2347 - 2347
Published: Dec. 20, 2024
Enabling
technologies
(KETs)
offer
transformative
potential
for
agriculture
by
addressing
major
challenges
such
as
climate
change,
resource
efficiency,
and
sustainable
development
across
economic,
social,
environmental
dimensions.
However,
KET
adoption
is
often
limited
high
R&D
requirements,
rapid
innovation
cycles,
investment
costs,
cultural
or
training
barriers,
especially
among
small
agricultural
businesses.
Sicily’s
sector,
already
strained
pandemic-related
economic
setbacks
inflationary
pressures,
faces
additional
barriers
in
adopting
these
technologies.
To
investigate
develop
viable
solutions,
the
ARIA
Living
Lab
(Agritech
Research
Innovation
Environment)
was
established
within
PNRR
framework.
A
qualitative
approach
used,
involving
documentary
analysis
data
from
stakeholders
Sicilian
agriculture.
This
enabled
an
in-depth
exploration
of
sector-specific
needs,
infrastructure,
socio-economic
factors
influencing
adoption.
The
highlighted
that
differ
significantly
sectors
(citrus,
olive,
wine),
with
public
incentives
digital
infrastructure
playing
key
roles.
a
persistent
lack
technical
skills
farmers
reduces
effectiveness
innovations.
findings
suggest
integrated
approach—combining
targeted
incentives,
training,
enhanced
infrastructure—is
essential
transition
to
KETs.
Future
research
should
examine
collaborative
efforts
between
farms
tech
providers
evaluate
impact
policies
promoting
widespread,
informed
enabling
Language: Английский
Climate and soil conditions shape farmers’ climate change adaptation preferences
Christian Stetter,
No information about this author
Carla Cronauer
No information about this author
Agricultural Economics,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 23, 2024
Abstract
Climate
change
poses
a
significant
threat
to
agriculture
and
challenges
farmers’
adaptive
capacity.
Understanding
how
farmers
evaluate
prioritize
different
climate
adaptation
measures
under
consideration
of
their
natural
environment
is
crucial
yet
widely
overlooked.
This
study
determines
the
relative
importance
that
attach
explores
role
climatic
soil
conditions
in
this
context.
It
uses
best‐worst
scaling
experiment
with
German
arable
combination
geospatial
information.
Findings
reveal
preference
for
incremental
over
more
transformative
ones.
However,
preferences
varied
considerably
average
local
temperature,
precipitation,
quality.
The
finding
are
highly
diverse
context‐specific
calls
tailored
policies.
policymakers
have
thorough
understanding
preferences.
Based
on
results,
discusses
multiple
actions
can
take
incentivize
favor
effective
measures.
Language: Английский