Toward sustainability: Integrating experimental study and data-driven modeling for eco-friendly paver blocks containing plastic waste
REVIEWS ON ADVANCED MATERIALS SCIENCE,
Год журнала:
2024,
Номер
63(1)
Опубликована: Янв. 1, 2024
Abstract
Plastic
waste
(PW)
poses
a
significant
threat
as
hazardous
material,
while
the
production
of
cement
raises
environmental
concerns.
It
is
imperative
to
urgently
address
and
reduce
both
PW
usage
in
concrete
products.
Recently,
several
experimental
studies
have
been
performed
incorporate
into
paver
blocks
(PBs)
substitute
for
cement.
However,
testing
not
enough
optimize
use
plastic
pavers
due
resource
time
limitations.
This
study
proposes
an
innovative
approach,
integrating
with
machine
learning
ratios
PBs
efficiently.
Initially,
investigations
are
examine
compressive
strength
(CS)
sand
(PSPBs).
Varied
mix
proportions
different
sizes
employed.
Moreover,
enhance
CS
meet
minimum
requirements
ASTM
C902-15
light
traffic,
basalt
fibers,
sustainable
industrial
also
utilized
manufacturing
process
environmentally
friendly
PSPB.
The
highest
17.26
MPa
achieved
by
using
finest-size
particles
plastic-to-sand
ratio
30:70.
Additionally,
inclusion
0.5%
fiber,
measuring
4
mm
length,
yields
further
enhancement
outcome
significantly
improving
25.4%
(21.65
MPa).
Following
that,
extensive
record
established,
multi-expression
programming
(MEP)
used
forecast
model’s
projected
results
confirmed
various
statistical
procedures
external
validation
methods.
Furthermore,
comprehensive
parametric
sensitivity
conducted
assess
effectiveness
MEP-based
proposed
models.
analysis
demonstrates
that
size
fiber
content
primary
factors
contributing
more
than
50%
accuracy
demonstrating
comparable
pattern
results.
indicate
formulation
exhibits
high
precision
R
2
0.89
possesses
strong
ability
predict.
provides
graphical
user
interface
increase
significance
ML
practical
application
handling
management.
main
aim
this
research
reuse
promote
sustainability
economic
benefits,
particularly
producing
green
environments
integration
investigations.
Язык: Английский
Cobalt Oxide-Decorated on Carbon Derived from Onion Skin Biomass for Li-Ion Storage Application
Metals,
Год журнала:
2024,
Номер
14(2), С. 191 - 191
Опубликована: Фев. 2, 2024
Onion
waste,
particularly
onion
skin,
is
a
widely
generated
waste
material,
and
harnessing
its
potential
for
energy
storage
aligns
with
sustainable
development
goals.
Despite
the
high
specific
surface
area
exhibited
by
biocarbon
derived
from
Li-ion
performance
not
desirable.
In
this
study,
purple
skin
serves
as
substrate
accommodating
cobalt
oxide
(Co3O4)
through
hydrothermal
method,
employing
Co(NO3)2·6H2O
at
various
concentrations,
without
prior
activation
using
KOH
treatment.
The
resulting
samples
undergo
comprehensive
analyses,
including
phase,
morphological,
surface,
electrochemical
characterizations.
Co3O4
decoration
on
activated
carbon
synthesized
concentration
of
1
M,
reveals
porous
structure
702
m2/g,
featuring
predominant
pore
sizes
less
than
5
nm.
Significantly,
sample
surpasses
that
alternative
samples,
demonstrating
remarkable
reversible
capacity
451
mAh/g
even
after
500
cycles
an
elevated
current
density
2000
mAh/g.
charge
transfer
resistance
(110.3
Ω)
found
to
be
substantially
lower
prepared
carbonized
biomass
activation.
This
research
introduces
innovative
approach
leveraging
template
decoration,
thereby
fabricating
high-performance
anodes
lithium-ion
batteries.
Язык: Английский
Machine Learning for Waste-to-Energy: Optimization and Predictive Analytics
Communications in computer and information science,
Год журнала:
2025,
Номер
unknown, С. 70 - 82
Опубликована: Янв. 1, 2025
Язык: Английский
Park Development, Potential Measurement, and Site Selection Study Based on Interpretable Machine Learning—A Case Study of Shenzhen City, China
ISPRS International Journal of Geo-Information,
Год журнала:
2025,
Номер
14(5), С. 184 - 184
Опубликована: Апрель 24, 2025
Scientific
site
selection
for
urban
parks
is
an
important
way
to
increase
resilience
and
safeguard
people’s
well-being.
Aiming
at
the
lack
of
systematic
consideration
in
traditional
park
siting
research,
this
study
utilizes
geographically
weighted
regression
explore
various
characteristic
factors
affecting
spatial
distribution
parks,
based
on
this,
combines
random
forest
model
interpretable
accurately
assess
potential
land
Shenzhen
provide
basis
selection.
The
indicates
that:
①
Shenzhen’s
exhibit
complex
differentiation
characteristics
terms
natural
landscape
elements
intensity
economic
activities;
②
(GWRF)
has
better
learning
generalization
capabilities
compared
(RF)
model,
average
accuracy
GWRF
improved
by
0.04
RF
model;
③
park’s
development
divided
according
results
with
52.01%
denoted
as
incubation
zone,
21.15%
accumulation
8.25%
growth
18.59%
core
zone;
④
Through
interpretability
analysis,
it
identified
that
vegetation
coverage,
density
tourist
attractions
or
points
interest
(POI),
slope,
elevation,
nighttime
light
are
most
significant
potential,
while
distance
roads
bodies
water
least
influential
factors.
research
systematically
explores
a
quantitative
evaluation
framework
opening
new
theoretical
pathways
practical
paradigms
sustainable
planning
under
“Park
City”
concept.
Язык: Английский
Waste-to-Energy Solutions Harnessing IoT and ML for Sustainable Power Generation in Smart Cities
Advances in computational intelligence and robotics book series,
Год журнала:
2024,
Номер
unknown, С. 125 - 146
Опубликована: Март 22, 2024
This
chapter
explores
waste-to-energy
(WtE)
solutions
empowered
by
the
integration
of
internet
things
(IoT)
and
machine
learning
(ML)
for
sustainable
power
generation
in
smart
cities.
By
leveraging
IoT
sensors,
real-time
data
acquisition
optimizes
waste
management
processes,
ML
algorithms
enhance
operational
efficiency.
The
potential
impact
these
technologies
on
WtE's
future
includes
predictive
maintenance,
sorting
automation,
adaptive
energy
production.
role
WtE
cities
extends
to
decentralized
generation,
integrated
management,
fostering
circular
economy
principles.
study
calls
further
research
adoption
practices
propel
as
a
key
component
landscape
resilient
urban
environments.
Язык: Английский
Advanced Waste Seclusion and Chucking System Using Deep Learning Techniques
Deleted Journal,
Год журнала:
2024,
Номер
20(4s), С. 2210 - 2216
Опубликована: Апрель 8, 2024
Any
material
that
is
undesirable
or
unusable
considered
waste.
Waste
can
be
in
any
form
(Liquid,
solid
gas)
but
generally,
waste
a
form.
There
are
various
types
of
like
paper,
displeasing
food,
torn
clothes,
dried
plants,
kitchen
waste,
etc.,
Skin
disease,
diarrhea,
tuberculosis,
whooping
cough,
pneumonia
etc..,
some
other
common
diseases
spread
due
to
immoral
management.
Separating
allows
us
salvage
more
items,
preventing
their
scraping
landfills.
By
reducing
landfills
disposal
Segregating
important
not
only
reduce
its
impact
on
the
environment
also
prevent
health
issues
arise
from
and
toxins.
Although
problem
segregation
big
challenge,
there
several
methods
for
automatic
segregation,
which
eliminates
need
human
hands.
The
proposed
system
utilizes
Faster
R-CNN
algorithms
segregate
into
bio-degradable
non-biodegradable
categories
which,
effectively
eliminating
involvement
process.
This
method
employs
artificial
intelligence
techniques
achieve
segregation.
Язык: Английский
Leveraging Waste-to-Energy Technologies for Sustainable Development: A Comprehensive Review
Shekhar Sharma,
V. Mallikarjuna Reddy,
Gowtham Raj R
и другие.
E3S Web of Conferences,
Год журнала:
2024,
Номер
529, С. 02010 - 02010
Опубликована: Янв. 1, 2024
The
challenging
situations
of
growing
energy
consumption,
waste
collection
and
destruction
the
surroundings
had
been
made
greater
apparent
by
means
explosive
rise
global
population
commercial
interest.
Modern
techniques
based
on
5R
principle
(Recycle,
Reduce,
Reuse,
Recover,
Repaired)
are
critical
to
efficaciously
addressing
these
problems.
One
promising
way
turn
non-recyclable
into
beneficial
power
assets
is
waste-to-power
(WtE)
conversion
method.
This
work
presents
a
comprehensive
evaluation
various
WtE
technologies,
consisting
pyrolysis,
gasoline
production,
anaerobic
digestion,
combustion,
highlighting
their
ability
reduce
associated
troubles.
Furthermore,
as
supplementary
for
sustainable
control
methods,
it
seems
at
combination
progressed
(IWM),
higher
landfill
mining,
substances
(SSM).
impact
environment
changes
evaluated
through
radical
current
research
technology
advancements,
emphasizing
decreases
in
utilization,
GHG
emissions,
promoting
renewable
resources.
consequences
highlight
essential
role
that
generation
performs
accomplishing
efficiency
improvements,
cleaner
development
round
financial
structure.
Ultimately,
article
makes
suggestions
future
studies
initiatives
coverage
recommendations
intended
optimize
economic
environmental
gains
from
deployments.
Язык: Английский
A Novel Evaluation Model of Subway Station Adaptability Based on Combination Weighting and an Improved Extension Cloud Model
Buildings,
Год журнала:
2024,
Номер
14(9), С. 2867 - 2867
Опубликована: Сен. 11, 2024
The
rational
selection
of
subway
station
locations
is
an
interdisciplinary
problem
encompassing
architecture,
transportation,
and
other
fields.
Few
evaluation
index
systems
quantitative
methods
exist
for
choosing
locations;
thus,
this
paper
establishes
a
novel
framework.
Overall,
21
indicators
covering
the
construction
operation
phases
are
selected
by
literature
review,
providing
basis
planning
decision
makers.
Projection
Pursuit
Method
(PPM)
Bald
Eagle
Search
(BES)
algorithm
employed
to
assign
objective
weights.
Continuous
Ordered
Weighted
Averaging
(COWA)
operator
utilized
obtain
subjective
A
combination
weighting
method
used
based
on
game
theory
improve
accuracy
weight
calculation.
Game
extension
cloud
applied
develop
improved
model
evaluate
suitability
optimal
entropy.
We
conduct
case
study
15
stations
Chengdu
Metro
Line
11,
China.
results
reveal
that
coordination
development
plans,
alignment
with
land
use
plan,
regional
population
density
most
crucial
tertiary
should
be
considered
in
selecting
locations.
These
findings
agree
actual
conditions,
demonstrating
scientific
validity
proposed
method,
which
outperforms
classical
methods.
efficient
feasible
Язык: Английский