Research on Intelligent Information Processing and Decision Support Methods in Modern Agricultural and Forestry Economic Management
Applied Mathematics and Nonlinear Sciences,
Journal Year:
2025,
Volume and Issue:
10(1)
Published: Jan. 1, 2025
Abstract
With
the
rapid
development
of
information
technology,
modern
agroforestry
economic
management
is
gradually
integrating
intelligent
processing
and
decision
support
system
to
improve
efficiency
quality
making.
In
this
study,
a
for
economy
developed,
which
uses
convolutional
neural
networks
an
improved
coordinated
attention
mechanism
module
(MA)
as
method.
The
algorithms
such
fuzzy
hierarchical
analysis
entropy
weight
method
are
integrated
make
comprehensive
judgment
on
decisions
related
agroforestry.
in
paper
has
reasoning
accuracy
100%
fostering
98.47%
For
projects,
results
calculated
by
consistent
with
given
experts.
technology
selected
99.62%
predicting
yield
agricultural
forestry
cash
crop
specific
area.
can
optimize
planting
area
crops
higher
benefits.
conclusion,
using
decision-making
promote
sustainable
economy.
Language: Английский
Research on the Optimization of National Governance System Based on Data Science under the Perspective of Marxism
Applied Mathematics and Nonlinear Sciences,
Journal Year:
2025,
Volume and Issue:
10(1)
Published: Jan. 1, 2025
Abstract
Data
science
can
promote
the
intelligence
of
national
governance
methods,
and
enhance
efficiency
effectiveness
through
incorporation
big
data
collection
processing
intelligent
decision-making
system.
This
paper
systematically
utilizes
a
variety
methods
to
study
analyze
optimization
strategy
system
under
Marxist
perspective.
It
evaluates
effect
digital
transformation
implemented
in
place
A
by
constructing
evaluation
index
system,
provides
focus
indicators
process
using
fuzzy
hierarchical
analysis.
The
average
coefficient
variation
squared
for
Digital
infrastructure,
Agricultural
digitization,
Governance
digitization
is
0.734,
0.876,
0.775,
respectively,
which
better
discriminatory
ability.
Experts
showed
different
emphasis
on
indicators,
with
“Product
network
sales
rate”
scoring
lowest
at
78.282.
After
implementing
strategy,
ecological
level
Site
has
been
increasing
year
year.
And
based
gets
consistent
satisfaction
from
residents,
comprehensive
rating
about
4.26.
theoretical
support
empirical
enlightenment
new
era.
Language: Английский
A Multi-Criteria Forest Fire Danger Assessment System on GIS Using Literature-Based Model and Analytical Hierarchy Process Model for Mediterranean Coast of Manavgat, Türkiye
Sustainability,
Journal Year:
2025,
Volume and Issue:
17(5), P. 1971 - 1971
Published: Feb. 25, 2025
Forest
fires
pose
significant
environmental
and
economic
risks,
particularly
in
fire-prone
regions
like
the
Mediterranean
coast
of
Türkiye.
This
study
presents
a
comprehensive
Fire
Danger
Assessment
System
(FoFiDAS),
by
integrating
Geographic
Information
Systems
(GIS),
literature-based
model,
Analytical
Hierarchy
Process
(AHP),
machine
learning
(ML)
to
improve
forest
fire
danger
classification.
Both
models
integrate
13
key
parameters
identified
through
literature.
A
comparison
these
revealed
53%
overlap
classifications.
While
AHP
based
on
expert-weighted
assessment,
provided
more
structured
localized
classification,
model
relied
broader
scientific
data
but
lacked
adaptability.
Pearson
correlation
analysis
demonstrated
strong
between
classifications
historical
occurrences,
with
scores
0.927
(AHP)
0.939
(literature-based).
Further
ROC
confirmed
predictive
performance
both
models,
yielding
AUC
values
0.91
0.9121
for
respectively.
Five
ML
algorithms
were
used
validate
classification
performances,
Artificial
Neural
Network
(ANN)
achieving
highest
accuracy
(86.5%).
The
ANN
algorithm
exceeded
0.93
each
class,
F1-Score
was
above
0.85.
FoFiDAS
offers
reliable
tool
supporting
early
intervention
decision
making.
Language: Английский