Machine learning techniques for predicting the peak response of reinforced concrete beam subjected to impact loading
Results in Engineering,
Journal Year:
2024,
Volume and Issue:
unknown, P. 103135 - 103135
Published: Oct. 1, 2024
Language: Английский
A Review on Application of Machine Learning Techniques in Seismic Analysis of Timber Structures
Construction technologies and architecture,
Journal Year:
2025,
Volume and Issue:
17, P. 139 - 147
Published: April 15, 2025
In
the
last
two
decades,
great
progress
in
Machine
Learning
can
be
seen
various
fields
of
structural
engineering
including
seismic
analysis.
This
paper
focuses
on
cross-filed
(ML)
and
provides
an
overview
different
ML
techniques
been
used
analysis
studies,
compare
these
their
application
to
study
response
timber
structures.
The
comparison
common
supervised
this
are
Multi
Linear
Regression,
Regression
Tree,
Forest,
K
Nearest
Neighbor,
Support
Vector
Artificial
Neural
Networks.
recent
increase
studies
is
largely
focused
Reinforced
Concrete
(RC)
structures
but
its
for
behavior
still
explored.
Timber
considered
as
best
performing
material
under
strong
ground
motions.
However,
problems
associated
with
lack
experimental
data,
standard
numerical
models
design
codes.
It
has
observed
that
domain
new
increasingly
dynamic
area
high
impact
result
where
horizons
research
topics
waiting
investigated.
review
demonstrated
potential
improving
prediction
performance
by
use
ML.
These
methods
allow
more
efficient
accurate
modelling
complex
than
traditional
methods.
Language: Английский
Predicting Pull-out Strength and Failure Modes of Metal Anchors Embedded in Masonry Structures Using Explainable Machine Learning Models and Empirical Equations
Aryan Baibordy,
No information about this author
Mohammad Yekrangnia
No information about this author
Results in Engineering,
Journal Year:
2025,
Volume and Issue:
26, P. 105287 - 105287
Published: May 11, 2025
Language: Английский
Machine learning study for three-dimensional magnetohydrodynamics Casson fluid flow with Cattaneo-Christov heat flux using linear regression technique: Application in engineering science and technology
Engineering Applications of Artificial Intelligence,
Journal Year:
2025,
Volume and Issue:
156, P. 111159 - 111159
Published: May 23, 2025
Language: Английский