Buildings,
Год журнала:
2024,
Номер
14(5), С. 1255 - 1255
Опубликована: Апрель 29, 2024
In
the
exploration
of
sustainable
construction
materials,
application
ferronickel
slag
(FNS)
in
creating
pervious
concrete
has
been
investigated,
considering
its
potential
to
meet
dual
requirements
mechanical
strength
and
fluid
permeability.
To
elucidate
statistical
properties
models
for
predicting
performance
FNS-composited
with
different
sizes
aggregates
mixtures,
a
series
experiments,
including
54
kinds
mixtures
three
aggregate,
were
conducted.
The
focus
was
on
measuring
compressive
permeability
coefficient.
results
indicate
that
decreases
increase
aggregate
size,
while
coefficient
increases
size.
Through
normalization,
variability
these
quantitatively
analyzed,
revealing
coefficients
variation
concrete’s
overall
at
0.166,
0.132,
0.150,
respectively.
Predictive
developed
using
machine
learning
techniques,
such
as
Linear
Regression,
Support
Vector
Machines,
Regression
Trees,
Gaussian
Process
Regression.
These
demonstrated
proficiency
forecasting
