Centralized and Decentralized Approach to Monsoon Precipitation Forecasting in Pakistan
VFAST Transactions on Software Engineering,
Год журнала:
2025,
Номер
13(1), С. 72 - 87
Опубликована: Март 4, 2025
Rainfall,
is
one
of
the
most
important
meteorological
factors
that
affects
many
parts
our
everyday
lives
including
crop
productivity,
water
quality,
livestock
availability,
hydroelectric
power
generation
to
name
a
few.
Rainfall
prediction
can
significantly
contribute
boosting
economy
by
enabling
better
planning,
risk
management,
and
resource
allocation
in
various
industrial
sectors.
In
this
study,
forty
years
monsoon
precipitation
data
gathered
for
39
stations
across
five
zones
Pakistan.
We
propose
multi-step
Long
Short-Term
Memory
(LSTM)-based
model
capable
forecasting
Monsoon
yearly
data.
Three
LSTM
models
stack,
bidirectional
convolutional
are
applied
on
dataset
performance
these
analysed
using
centralized
decentralized
approach.
It
observed
RMSE
score
strategy
was
found
than
approach,
whereby
100%
had
lower
as
compared
one.
Moreover,
approach
78.7%
different
exhibited
R2
>
0.9
values
indicating
general
fit
model.
Язык: Английский
Integrated water management and agroforestry planning in the Kulsi river basin: a data-driven decision-making approach
Agroforestry Systems,
Год журнала:
2025,
Номер
99(5)
Опубликована: Апрель 28, 2025
Язык: Английский
Blockchain Technology Adoption for Agriculture, Manufacturing, Services, Knowledge, Culture, and Research: A Systematic Literature Review
WSEAS TRANSACTIONS ON SYSTEMS,
Год журнала:
2025,
Номер
24, С. 229 - 278
Опубликована: Май 6, 2025
Since
FinTech
had
the
most
potential
in
business,
economics,
and
knowledge
disciplines,
study's
major
goal
was
to
address
contributions
of
Blockchain
technology
adoption
(BCT/BCA)
six
knowledge,
culture,
research
areas.
To
ensure
that
on
subject
accessed
pertinent
publications
were
found,
vetted,
examined,
PRISMA
technique
-a
model
for
systematic
literature
reviews
(SLRs)-
employed
this
investigation.
The
results
show
BCA
improves
organizational
procedures,
performance,
fidelity,
integrity,
trust
businesses,
cultures,
projects
with
a
disrupting
financial
(FinTech)
mindset.
It
also
enhances
corporate
transaction
transparency
scalability,
big
data,
same-data,
information
sharing,
prevents
fraud
fraudulence
suspension
cyber-hacking
protection.
Additionally,
implementation
smart
contracts
offers
ESG
sustainability
benefits.
This
hybrid
methodology,
blending
together
qualitative
analysis
SLR.
All
789
chosen
initial
step
underwent
quantitative
analysis,
eight
cited
papers
passed
screening
process
examination.
study
sequence
is
composed
three
layers:
(i)
factors
function
as
functionality,
(ii)
possibilities
problems
related
variables,
(iii)
contributions,
consequences,
outlook
issues-
defined
paper
projected
Furthermore,
significant
contribution
thought
be
managers'
ability
consult
suggested
insightful
information,
economic
difficulties,
estimation.
Scholars,
researchers,
managers,
practitioners
will
all
benefit
from
study.
Язык: Английский
Trend Analysis of Rainfall for Multi-Purpose Water Resources Projects Using Machine Learning Predictive Model-ARIMA
SN Computer Science,
Год журнала:
2024,
Номер
5(8)
Опубликована: Ноя. 29, 2024
Язык: Английский
AI-Based Short-Term Precipitation Prediction in Precision Agriculture
Опубликована: Июль 15, 2024
Язык: Английский
Regulatory mechanisms in agroecosystems: A retrospective and forecast of spatial and temporal dynamics of precipitation as a factor of crop yield
Regulatory Mechanisms in Biosystems,
Год журнала:
2024,
Номер
15(4), С. 688 - 695
Опубликована: Окт. 12, 2024
The
research
tested
the
hypothesis
that
climate
of
studied
area
has
property
spatial
and
temporal
regularity,
this
regularity
is
hierarchically
organized,
which
makes
it
possible
to
predict
state
in
coming
decades.
practical
aspect
information
obtained
assessment
prospects
for
changes
yields
most
common
crops
region.
variability
precipitation
between
years
1960
2023,
soil
properties
landscape
cover
structure
were
investigated
within
10
administrative
regions
northern
northwestern
Ukraine.
This
region
covers
Polissia
Forest-Steppe
geographical
zones.
MEM
variables
able
explain
95.1%
precipitation.
ANOVA
revealed
8
canonical
axes
statistically
significant.
contribution
explanation
different,
allows
us
identify
hierarchical
main
patterns
RDA1
RDA2
represent
large-scale
component
variability.
indicates
differentiation
meridional
direction
with
allocation
eastern
western
sectors
denoting
correlated
land
types.
did
not
correlate
properties,
but
had
a
positive
correlation
proportion
broadleaf
forests
mosaic
herbaceous
shrubs
cover.
axis
negative
agricultural
land.
was
positively
organic
matter
sand
content,
negatively
clay
silt
content.
increased
an
increase
broadleaf,
coniferous
or
mixed
vegetation
structure.
decreased
sparse
RDA3
independent
content
area,
shrubs,
forests.
RDA4
increasing
proportions
rainfed
cover,
RDA5
crops,
RDA6
RDA7
RDA8
soil.
modelling
dynamics
over
more
than
60
can
be
carried
out
using
eight
AEM
predictors,
different
frequencies
variable
amplitudes
time.
If
we
assume
established
oscillatory
will
continue
decades,
then
these
predictors
extended
time
interest
regression
model
used
obtain
forecast
near
future.
downward
trend
precipitation,
mainly
areas
developed
agriculture.
Язык: Английский