Engineering Construction & Architectural Management,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 10, 2025
Purpose
The
objective
of
this
study
is
to
accurately
predict
the
cost
green
buildings
provide
quantifiable
criteria
for
investment
decisions
from
investors.
Design/methodology/approach
This
proposes
a
hybrid
prediction
model
ML-based
GBPs
and
obtains
parameters
(PPs)
associated
with
project
characteristics
through
data
mining
(DM)
techniques.
integrates
principal
component
analysis
(PCA)
method
perform
parameter
dimensionality
reduction
(PDR)
on
large
number
raw
variables
independent
characteristic
terms.
Moreover,
support
vector
machine
(SVM)
algorithm
improved
optimize
results
integrated
prediction.
Findings
show
that
mean
absolute
relative
errors
proposed
in
are
equal
39.78
0.02,
respectively,
which
much
lower
than
those
traditional
SVM
MRA
model.
also
achieved
better
accuracy
(
R
2
=
0.319)
superior
different
Originality/value
Theoretically,
developed
can
reliably
while
capturing
GBPs,
bold
attempt
at
comprehensive
approach.
Practically,
provides
developers
new
capable
costs
projects
ambiguous
definitions
complex
characteristics.
Sustainability,
Год журнала:
2024,
Номер
16(10), С. 3895 - 3895
Опубликована: Май 7, 2024
Under
the
backdrop
of
China’s
national
strategy
to
achieve
carbon
neutrality
by
2060,
efforts
are
underway
across
governmental,
corporate,
societal,
and
individual
sectors
actively
explore
energy-saving
renovations
in
existing
buildings.
Given
that
residential
buildings
constitute
a
significant
proportion
total
energy
consumption
throughout
lifecycle
China,
sustainable
renovation
structures
can
contribute
significantly
implementing
emission
reduction
policies.
While
there
exists
plethora
technological
means
market
aimed
at
improving
performance
buildings,
still
needs
be
more
systematic
discussion
on
framework
for
Chinese
with
knowledge
dissemination
needing
cohesive.
In
this
context,
paper
provides
comprehensive
review
field,
utilizing
bibliometric
methods.
Through
selected
peer-reviewed
literature
from
Web
Science
Scopus
databases,
study
focuses
categorizing
process
into
three
main
stages:
renovation,
building
simulation
suitability
assessment.
The
also
reviews
research
methods
adopted
previous
researchers
assessment
stages,
considering
various
optimization
algorithms,
variables,
objectives,
software
tools.
Subsequently,
synthesizes
comprising
these
stages
combined
different
aiming
assist
policymakers,
designers,
gaining
understanding
implementation
status
identifying
barriers
implementation,
formulating
efficient
policies
strategies
future.
Engineering Construction & Architectural Management,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 10, 2025
Purpose
The
objective
of
this
study
is
to
accurately
predict
the
cost
green
buildings
provide
quantifiable
criteria
for
investment
decisions
from
investors.
Design/methodology/approach
This
proposes
a
hybrid
prediction
model
ML-based
GBPs
and
obtains
parameters
(PPs)
associated
with
project
characteristics
through
data
mining
(DM)
techniques.
integrates
principal
component
analysis
(PCA)
method
perform
parameter
dimensionality
reduction
(PDR)
on
large
number
raw
variables
independent
characteristic
terms.
Moreover,
support
vector
machine
(SVM)
algorithm
improved
optimize
results
integrated
prediction.
Findings
show
that
mean
absolute
relative
errors
proposed
in
are
equal
39.78
0.02,
respectively,
which
much
lower
than
those
traditional
SVM
MRA
model.
also
achieved
better
accuracy
(
R
2
=
0.319)
superior
different
Originality/value
Theoretically,
developed
can
reliably
while
capturing
GBPs,
bold
attempt
at
comprehensive
approach.
Practically,
provides
developers
new
capable
costs
projects
ambiguous
definitions
complex
characteristics.
