This
study
addresses
the
issue
of
increasing
energy
consumption
for
household
hot
water
production,
emphasizing
significance
incorporating
solar
to
lower
this
demand.
topic
is
critical
in
light
need
minimize
reliance
on
traditional
sources
while
also
limiting
environmental
effect.
The
assesses
performance
an
individual
heater
built
average
family,
with
a
focus
efficiency.
technology
used
involves
integration
optimal
tracking
system,
which
capable
autonomously
altering
orientation
thermal
panels
during
day,
capture.
dynamic
change
increased
efficiency
heating
system
by
around
13%,
demonstrating
efficacy
strategy.
In
end,
shows
that
using
can
result
significant
savings
and
improve
heaters.
novelty
work
improvement
tracking,
goes
beyond
standard
static
systems
commonly
explored
allowing
real-time
adjustment
maximize
utilization
energy.
Results in Engineering,
Год журнала:
2024,
Номер
23, С. 102584 - 102584
Опубликована: Июль 20, 2024
Irrigation
is
a
crucial
component
of
the
agriculture
industry.
The
gross
domestic
output
India
about
15
%
derived
from
its
farmers.
Crop
failure
common
among
farmers,
primarily
because
inadequate
irrigation
techniques
and
irregular
power
water
supplies.
To
begin
with,
survey
farmers
various
parts
was
undertaken
in
this
regard,
results
indicated
that
most
them
lacked
an
effective
system.
An
inventive
solar-powered
system
devised
deployed
to
address
problem
includes
automated
Internet
Things
(IoT)
This
IoT
system,
which
functions
based
on
moisture
content
soil,
plays
role
ensuring
crops
receive
right
amount
at
time.
Furthermore,
PV
pumping
addresses
issues
Indian
climate
conditions,
including
composite,
warm
humid,
cold,
moderate,
hot,
dry.
locations
chosen
for
these
conditions
are
Jaisalmer
Rajasthan,
Bangalore
Karnataka,
Itanagar
Arunachal
Pradesh,
Patna
Bihar,
Amaravati
Andhra
Pradesh.
Performance
ratios
range
0.514
0.739,
pump
efficiencies
61
88.80
%,
57.10
%–58.60
respectively.
Challenges in Sustainability,
Год журнала:
2024,
Номер
12(1), С. 1 - 17
Опубликована: Апрель 30, 2024
Climate
change
(CC)
represents
a
paramount
environmental
challenge,
necessitating
the
deployment
of
sustainable,
low-carbon
strategies
particularly
in
developing
regions
such
as
Africa.
This
study
introduces
novel
decision-making
framework
aimed
at
enhancing
prioritization
policies
to
combat
adverse
effects
CC.
The
proposed
two-stage
model
employs
integration
Step-Wise
Weight
Assessment
Ratio
Analysis
(SWARA)
and
Weighted
Aggregated
Sum
Product
(WASPAS)
under
spherical
fuzzy
(SF)
conditions
address
strategic
sequencing
sustainable
policies.
Initially,
SF-SWARA
is
utilized
ascertain
relative
significance
diverse
criteria.
Subsequently,
SF-WASPAS
method
ranks
these
policies,
facilitating
informed
decision-making.
primary
obstacles
identified
include
limited
institutional
capacity,
insufficient
financial
resources,
technological
constraints,
for
which
alternatives
are
proposed.
Moreover,
rigorous
sensitivity
comparative
analyses
affirm
model's
applicability.
By
systematically
delineating
prioritizing
necessary
this
contributes
significantly
scholarly
discourse
on
climate
mitigation
(CM)
an
African
context.
Case Studies in Thermal Engineering,
Год журнала:
2024,
Номер
61, С. 104853 - 104853
Опубликована: Июль 17, 2024
Predicting
PV
system
electricity
output
is
necessary
for
daily
operational
management
and
annual
power
planning
when
integrating
solar
collector-based
photovoltaic
(PV)
stations
into
micro
grids.
Tilting
the
panels
at
ideal
angle
to
maximize
energy
capture
station
production.
This
optimal
tilt
(OTA)
must
be
predicted
as
it
a
nonlinear
function
of
total
radiation,
diffuse
direct
radiation.
research
explores
use
feature
selection-based
artificial
neural
networks
(ANN)
with
various
machine
learning
algorithms
predict
OTA
systems
specific
locations,
aiming
in
The
study
identifies
global
clarity
index,
radiation
on
inclined
surfaces
most
critical
inputs
predicting
OTA,
while
extraterrestrial
deemed
least
significant.
Implementing
appropriate
input
variables
significantly
enhanced
prediction
accuracy
from
38.59
%
90.72
%.
Among
evaluated,
Elman
network
demonstrated
greatest
improvement.
Information,
Год журнала:
2025,
Номер
16(3), С. 198 - 198
Опубликована: Март 4, 2025
This
paper
addresses
the
challenges
in
extracting
content
words
within
domains
of
natural
language
processing
(NLP)
and
artificial
intelligence
(AI),
using
sustainable
development
goals
(SDGs)
corpora
as
verification
examples.
Traditional
corpus-based
methods
term
frequency-inverse
document
frequency
(TF-IDF)
method
face
limitations,
including
inability
to
automatically
eliminate
function
words,
effectively
extract
relevant
parameters’
quantitative
data,
simultaneously
consider
range
parameters
evaluate
terms’
overall
importance,
sort
at
corpus
level.
To
overcome
these
this
proposes
a
novel
based
on
weighted
aggregated
sum
product
assessment
(WASPAS)
technique.
NLP
integrates
word
elimination
method,
an
machine,
WASPAS
technique
improve
extraction
ranking
words.
The
proposed
efficiently
extracts
considers
substantial
ranks
level,
providing
comprehensive
overview
significance.
study
employed
target
from
Web
Science
(WOS),
comprising
35
highly
cited
SDG-related
research
articles.
Compared
competing
methods,
results
demonstrate
that
outperforms
traditional
