The impact of power system characteristics on the energy consumption of a steel plant
E3S Web of Conferences,
Год журнала:
2024,
Номер
583, С. 05012 - 05012
Опубликована: Янв. 1, 2024
This
paper
presents
a
comprehensive
analysis
of
the
relationships
between
energy
consumption
and
various
factors
affecting
operation
power
system
steel
plant.
Given
growing
demand
for
electricity
necessity
to
transition
sustainable
sources,
studying
these
is
becoming
increasingly
relevant.
The
main
methods
used
in
research
include
correlation
factor
analysis,
which
help
identify
key
dependencies
patterns
behavior
systems.
study
covers
parameters
such
as
reactive
power,
load
type,
temporal
factors,
including
day
week
day's
status.
results
reveal
strong
relationship
lagging
well
significant
connections
with
other
variables,
type
characteristics.
These
highlight
importance
considering
resource
management.
Factor
identifies
several
influencing
consumption,
opening
new
opportunities
process
optimization
findings
emphasize
need
data
approach
effectively
manage
enhance
resilience
supply
work
practical
significance
companies
specialists
management,
can
be
develop
strategies
optimizing
improving
planning,
ensuring
reliability.
Overall,
this
contributes
understanding
dynamics
lays
foundation
future
field
development.
Язык: Английский
Statistical analysis of seasonal variations in pollutant concentrations in urban atmosphere
E3S Web of Conferences,
Год журнала:
2024,
Номер
592, С. 06010 - 06010
Опубликована: Янв. 1, 2024
In
the
context
of
global
climate
change
and
urbanization,
issue
air
quality
is
becoming
increasingly
relevant.
Air
pollution
poses
a
threat
to
human
health
ecosystems,
highlighting
need
for
monitoring
concentrations
pollutants.
This
study
examines
seasonal
variations
in
harmful
substances
urban
atmosphere
using
statistical
methods.
The
aim
research
analyze
time
series
data
on
carbon
monoxide
(CO),
nitrogen
oxide
(NO),
dioxide
(NO2),
sulfur
(SO2),
ozone
(O3),
ammonia
(NH3),
particulate
matter
(PM2.5
PM10).
Correlation
factor
analysis
are
employed
assess
relationships
between
pollutants
identify
underlying
factors.
collected
over
several
years
emphasizes
changes,
showing
that
pollutant
subject
significant
fluctuations
driven
by
both
natural
anthropogenic
results
can
be
used
develop
strategies
improving
predicting
impacts
population.
deepens
understanding
dynamics
atmospheric
its
dependence,
which
important
shaping
environmental
policy
management
decisions.
Язык: Английский
Modeling techniques for enhancing barrel-type part casting processes
E3S Web of Conferences,
Год журнала:
2024,
Номер
592, С. 05022 - 05022
Опубликована: Янв. 1, 2024
This
article
discusses
the
principles
of
modeling
casting
process
for
parts
-
“Barrel”.
A
detailed
overview
drawing
is
provided,
as
well
designed
3D
model
according
to
this
drawing.
The
values
allowances
machining
part
are
analyzed.
characteristic
obtained
alloy
presented,
on
basis
which
calculation
technological
yield
suitable
one
made.
At
end
article,
result
output
a
given.
Язык: Английский
Forecasting seismic activity using machine learning algorithms
E3S Web of Conferences,
Год журнала:
2024,
Номер
592, С. 05002 - 05002
Опубликована: Янв. 1, 2024
In
this
paper,
the
possibility
of
using
random
forest
method
to
predict
earthquake
locations
based
on
historical
data
was
studied.
The
aim
work
develop
a
model
capable
accurately
predicting
geographical
coordinates
earthquakes
in
India
and
adjacent
regions.
showed
high
accuracy
predictions,
which
is
confirmed
by
low
values
mean
quadratic
error
(MSE)
coefficients
determination
(R
2
).
Analysis
results
that
successfully
captures
patterns
able
regions
with
seismic
activity.
At
same
time,
areas
deviations
were
identified,
highlights
need
for
further
research
improve
increase
its
accuracy.
This
study
demonstrates
promise
machine
learning
methods
seismological
forecasting
tasks
can
serve
as
basis
creating
more
accurate
early
warning
systems.
Язык: Английский
Modeling the impact of pollinator biodiversity on the resilience of agricultural ecosystems
BIO Web of Conferences,
Год журнала:
2024,
Номер
141, С. 01028 - 01028
Опубликована: Янв. 1, 2024
This
study
focuses
on
examining
the
factors
that
influence
yield
of
wild
blueberries
(Vaccinium
spp.),
taking
into
account
ecological
and
agronomic
aspects.
In
context
climate
change
declining
pollinator
populations,
food
security
has
become
a
pressing
issue.
Successful
pollination
determines
quantity
quality
harvests,
including
berries.
The
research
utilized
data
habitat
characteristics
blueberries,
density
(honeybees,
bumblebees,
bees)
climatic
conditions
(temperature,
precipitation).
Statistical
methods,
such
as
correlation
factor
analysis,
were
applied
to
identify
relationships
between
influencing
factors.
results
showed
high
blueberry
yields
are
associated
with
presence
pollinators
conditions.
Positive
correlations
observed
seed
yield,
well
negative
clone
size
fruit
set.
These
findings
underscore
importance
diversity
optimal
highlights
need
preserve
biodiversity
optimize
practices
in
face
change.
can
be
used
develop
recommendations
for
improving
cultivation
methods
increasing
yields.
Язык: Английский
Application of neural networks to predict the quality of iron ore concentrate based on flotation data
E3S Web of Conferences,
Год журнала:
2024,
Номер
583, С. 01014 - 01014
Опубликована: Янв. 1, 2024
This
paper
presents
a
study
aimed
at
developing
and
testing
neural
network
model
for
predicting
the
percentage
of
silica
in
iron
ore
concentrate
obtained
during
flotation.
The
problem
precise
control
content
is
critical
mining
industry,
since
quality
final
product
and,
accordingly,
its
market
value
depend
on
it.
During
study,
data
was
collected
from
flotation
plant,
their
preliminary
processing
carried
out,
including
standardization
elimination
missing
values.
developed
included
two
hidden
layers
trained
real
data.
evaluation
showed
high
results,
which
confirmed
by
metrics
mean
square
error
(MSE),
absolute
(MAE)
coefficient
determination
(R
2
).
Additionally,
an
analysis
visualizations
residuals
predicted
values
accuracy
stability
model.
results
demonstrate
that
proposed
can
be
effectively
used
production
conditions
to
improve
process
industry.
Язык: Английский
Integration of IT solutions for resource management in environmentally sustainable agriculture
BIO Web of Conferences,
Год журнала:
2024,
Номер
145, С. 06008 - 06008
Опубликована: Янв. 1, 2024
This
article
presents
the
development
of
a
resource
management
system
for
environmentally
sustainable
agriculture.
The
main
purpose
is
to
optimize
use
water,
fertilizers
and
energy
in
agriculture,
which
significantly
reduces
negative
impact
on
environment
increases
production
efficiency.
includes
modules
soil
monitoring,
data
collection
resources
climatic
conditions,
as
well
analytical
components
processing
analysing
information
received.
An
important
element
user
interface,
allows
farmers
agronomists
receive
recommendations
allocation
based
up-to-date
forecasts.
work
highlights
current
challenges
such
systems,
including
complexity
technology
integration
need
affordable
solutions
various
types
farms.
also
discusses
prospects
further
research
aimed
at
improving
accuracy
forecasts,
expanding
monitoring
functions
adapting
small
proposed
makes
significant
contribution
oriented
providing
tool
contributing
achievement
environmental
protection
goals.
Язык: Английский
Decision support in reforestation through the analysis of soil and mycorrhiza data
BIO Web of Conferences,
Год журнала:
2024,
Номер
145, С. 06006 - 06006
Опубликована: Янв. 1, 2024
This
study
presents
an
analysis
of
key
biological
and
ecological
factors
affecting
the
growth
survival
tree
seedlings.
The
dataset
used
includes
information
on
soil
types,
levels
mycorrhizal
activity,
biochemical
compound
content,
light
availability,
other
environmental
parameters.
Special
attention
is
given
to
relationships
between
symbioses
(AMF,
EMF),
plant
physiological
characteristics,
conditions.
Correlation
cluster
methods
were
applied
data,
allowing
for
identification
groups
with
similar
characteristics
assessment
impact
various
their
survival.
results
emphasize
importance
microbial
interactions
indicators,
such
as
phenol
lignin
in
adaptation
trees
stressful
data
can
be
decision-making
reforestation,
including
optimizing
planting
conditions
selecting
most
resilient
species.
also
highlights
managing
microbiome
enhance
effectiveness
forest
ecosystem
restoration.
Язык: Английский
Optimizing planting schedules and land use through advanced weather monitoring systems
BIO Web of Conferences,
Год журнала:
2024,
Номер
145, С. 04030 - 04030
Опубликована: Янв. 1, 2024
This
article
explores
the
development
of
an
information
system
(IS)
designed
to
monitor
weather
conditions
and
optimize
planting
schedules
land
use
for
agricultural
activities.
Leveraging
advanced
modeling
techniques,
system’s
architecture
processes
are
meticulously
mapped
out
ensure
clarity
efficiency.
The
collects
data
from
ground-based
sensors,
satellite
imagery,
drones,
which
is
then
analyzed
provide
actionable
insights.
Key
components
include
WeatherDataCollector,
WeatherAnalyzer,
PlantingScheduleOptimizer,
NotificationManager.
Sequence
diagrams
illustrate
interactions
between
these
components,
collection
analysis
dissemination
recommendations.
enhances
decision-making
farmers,
improving
crop
yields
optimizing
while
mitigating
risks
associated
with
adverse
conditions.
By
integrating
robust
management
analytical
capabilities,
IS
provides
a
scalable
reliable
solution
modern
agriculture,
driving
innovation
sustainability
in
sector.
work
underscores
transformative
potential
technology
practices
management.
Язык: Английский
Analysis of soil suitability for agricultural needs using machine learning methods
BIO Web of Conferences,
Год журнала:
2024,
Номер
149, С. 01053 - 01053
Опубликована: Янв. 1, 2024
This
study
explores
the
application
of
machine
learning
methods
to
assess
soil
suitability
for
agricultural
purposes,
focusing
on
identifying
and
analysing
key
factors
that
influence
productivity
under
drought
conditions.
A
classification
model
was
developed
based
data
from
diverse
U.S.
regions,
which
included
critical
parameters
such
as
root
condition,
nutrient
availability,
toxicity,
oxygen
accessibility
plant
roots.
Correlation
analysis
identified
most
significant
impacting
suitability,
with
condition
availability
emerging
primary
determinants.
The
achieved
a
high
accuracy
98.81%,
demonstrating
its
effectiveness
in
predicting
across
varying
environmental
research
highlights
value
optimizing
practices
by
enabling
data-driven
assessment.
Moreover,
addresses
importance
accessible
cost-effective
collection
scaling
different
regions.
Despite
model’s
accuracy,
limitations
related
specificity
regional
variability
were
observed,
indicating
areas
future
improvement.
Expanding
additional
climatic
geographic
could
enhance
generalizability
applicability
settings.
Overall,
this
provides
insights
into
potential
support
sustainable
agriculture
efficient
land
management.
Язык: Английский