Development of a Hybrid Model for Risk Assessment and Management in Complex Road Infrastructure Projects
Applied Sciences,
Journal Year:
2025,
Volume and Issue:
15(5), P. 2736 - 2736
Published: March 4, 2025
During
the
execution
of
road
infrastructure
projects,
project
managers
face
significant
challenges,
including
financial,
technical,
regulatory,
and
operational
risks.
More
than
90%
projects
have
incurred
costs
exceeding
initial
estimates,
impacting
both
completion
timelines
efficiency
infrastructure.
Effectively
assessing
managing
these
risks
is
crucial
for
improving
outcomes
ensuring
sustainability
investments.
To
address
this
study
developed
a
hybrid
model
risk
assessment
management
in
projects.
The
quantifies
across
seven
key
categories:
Design,
External,
Resource,
Employer,
Contractor,
Engineer,
Project,
based
on
three
primary
input
factors:
Environment
coefficient,
Contractual
Design
coefficient.
Initially,
various
machine
learning
models,
linear
regression,
Random
Forest,
Gradient
Boosting,
Stacking
Models,
neural
networks,
were
applied
to
assess
predictions.
However,
due
specific
nature
dataset,
models
did
not
achieve
satisfactory
predictive
accuracy.
As
result,
fuzzy
logic
systems
(Mamdani
Sugeno)
employed,
demonstrating
superior
performance
modeling
occurrence
probabilities.
Comparative
analysis
between
two
approaches
revealed
that
Sugeno
provided
most
accurate
findings
highlight
benefits
applying
complex
providing
structured
framework
enhancing
decision-making
processes.
This
provides
methodology
accurately
predicting
safety,
efficiency,
long-term
sustainability.
Language: Английский
Predicting Extension of Time and Increasing Contract Price in Road Infrastructure Projects Using a Sugeno Fuzzy Logic Model
Mathematics,
Journal Year:
2024,
Volume and Issue:
12(18), P. 2852 - 2852
Published: Sept. 13, 2024
Road
infrastructure
plays
a
crucial
role
in
the
development
of
countries,
significantly
influencing
economic
growth,
social
progress,
and
environmental
sustainability.
Major
projects
are
frequently
challenged
by
substantial
risks
uncertainties,
leading
to
delays,
budget
overruns,
compromised
quality.
These
issues
can
undermine
viability
efficiency
projects,
making
effective
risk
management
essential
for
minimizing
negative
impacts
ensuring
project
success.
For
these
reasons,
study
was
conducted
using
Sugeno
fuzzy
logic
system
applied
completed
projects.
The
resulting
model
is
based
on
10
characteristics
provides
highly
accurate
predictions
Extension
Time
(EoT)
Increasing
Contract
Price
(ICP).
By
utilizing
this
model,
be
improved
through
more
forecasting
potential
delays
cost
overruns.
high
precision
enables
better
assessment
proactive
decision-making,
allowing
managers
implement
targeted
strategies
mitigate
optimize
outcomes.
Language: Английский