Perspectivas em Diálogo revista de educação e sociedade,
Journal Year:
2024,
Volume and Issue:
11(29), P. 166 - 183
Published: Dec. 19, 2024
O
gerenciamento
de
projetos
tem
se
consolidado
como
uma
metodologia
essencial
para
a
gestão
empreendimentos
em
diversas
áreas,
incluindo
construção
civil.
Este
estudo
teve
objetivo
avaliar
o
alinhamento
entre
formação
profissional
do
engenheiro
civil
e
as
demandas
mercado
trabalho
termos
projetos,
cinco
anos
após
identificação
lacuna
nesse
2018.
A
consistiu
na
análise
das
grades
curriculares
cursos
graduação
engenharia
no
Brasil,
com
foco
inclusão
disciplinas
projetos.
Os
resultados
indicam
que
identificada
diminuiu
significativamente,
concentração
regional
relativa
da
oferta
dessa
disciplina
foi
ligeiramente
reduzida
Instituições
Ensino
Superior
(IES)
privadas
não
é
mais
predominante.
Engineering Science & Technology Journal,
Journal Year:
2024,
Volume and Issue:
5(4), P. 1214 - 1230
Published: April 10, 2024
This
paper
explores
the
integration
of
AI
in
smart
drilling
technologies,
examining
its
applications,
benefits,
challenges,
and
future
prospects.
By
harnessing
power
AI,
technologies
enable
proactive
decision-making,
automation,
optimization
throughout
lifecycle.
From
well
planning
design
to
real-time
monitoring
control,
AI-driven
systems
improve
operational
performance,
reduce
risks,
maximize
resource
recovery.
Despite
facing
challenges
such
as
data
integration,
technology
adoption,
regulatory
compliance,
potential
benefits
are
substantial.
Enhanced
precision,
improved
safety,
increased
efficiency,
sustainable
practices
among
key
offered
by
these
technologies.
Looking
towards
future,
opportunities
for
further
innovation
advancement
abound,
including
development
advanced
algorithms,
with
IoT
big
analytics,
a
focus
on
environmental
sustainability.
embracing
innovation,
collaboration,
commitment
sustainability,
oil
gas
industry
can
unlock
new
growth
resilience
evolving
landscape
construction.
Smart
hold
promise
reshaping
construction,
paving
way
safer,
more
efficient,
operations
industry.
revolutionizing
industry,
offering
unprecedented
levels
precision
safety
integrating
artificial
intelligence
(AI)
into
processes,
optimize
parameters,
recovery..
sustainability.
Keywords:
drilling,
Artificial
(AI),
Oil
Efficiency,
Safety,
Sustainability.
Sustainability,
Journal Year:
2024,
Volume and Issue:
16(10), P. 4235 - 4235
Published: May 17, 2024
The
rapid
urbanization
of
Abha
and
its
surrounding
cities
in
Saudi
Arabia’s
mountainous
regions
poses
challenges
for
sustainable
secure
development.
This
study
aimed
to
identify
suitable
sites
eco-friendly
safe
building
complexes
amidst
complex
geophysical,
geoecological,
socio-economic
factors,
integrating
natural
hazards
assessment
risk
management.
Employing
the
Fuzzy
Analytic
Hierarchy
Process
(Fuzzy-AHP),
constructed
a
suitability
model
incorporating
sixteen
parameters.
Additionally,
Deep
Neural
Network
(DNN)
based
on
eXplainable
Artificial
Intelligence
(XAI)
conducted
sensitivity
analyses
assess
parameters’
influence
optimal
location
decision
making.
results
reveal
slope
as
most
crucial
parameter
(22.90%),
followed
by
altitude
land
use/land
cover
(13.24%),
emphasizing
topography
environmental
considerations.
Drainage
density
(11.36%)
rainfall
patterns
(9.15%)
are
also
significant
flood
defense
water
Only
12.21%
area
is
deemed
“highly
suitable”,
with
“no-build
zones”
designated
safety
protection.
DNN-based
XAI
demonstrates
positive
impact
variables
like
NDVI
municipal
solid
waste
generation
site
selection,
informing
management
ecological
preservation
strategies.
integrated
methodology
provides
actionable
insights
residential
development
Abha,
aiding
informed
making
balancing
urban
expansion
conservation
hazard
reduction.
Energies,
Journal Year:
2025,
Volume and Issue:
18(7), P. 1571 - 1571
Published: March 21, 2025
Wind
power
prediction
plays
a
crucial
role
in
enhancing
grid
stability
and
wind
energy
utilization
efficiency.
Existing
methods
demonstrate
insufficient
integration
of
multi-variate
features,
such
as
speed,
temperature,
humidity,
along
with
inadequate
extraction
correlations
between
variables.
This
paper
proposes
novel
multi-scale
method
named
variational
mode
decomposition
informer
(MSVMD-Informer).
First,
modal
module
is
designed
to
decompose
univariate
time-series
features
into
multiple
scales.
Adaptive
graph
convolution
applied
extract
scales,
while
self-attention
mechanisms
are
utilized
capture
temporal
dependencies
within
the
same
scale.
Subsequently,
feature
fusion
proposed
better
account
for
inter-variable
correlations.
Finally,
reconstructed
by
integrating
aforementioned
modules,
enabling
forecasting.
The
was
evaluated
through
comparative
experiments
ablation
studies
against
seven
baselines
using
public
dataset
two
private
datasets.
Experimental
results
that
our
achieves
optimal
metric
performance,
its
lowest
MAPE
scores
being
1.325%,
1.500%
1.450%,
respectively.
PeerJ Computer Science,
Journal Year:
2025,
Volume and Issue:
11, P. e2812 - e2812
Published: April 7, 2025
This
study
explores
the
complexities
of
enterprise
financial
management
by
optimizing
models
with
a
particular
focus
on
enhancing
risk
prediction
performance.
A
multi-objective
mathematical
model
is
first
developed
to
establish
key
optimization
goals,
including
cost
reduction,
improved
capital
utilization,
and
increased
economic
benefits.
systematically
defines
decision
variables
objectives,
providing
comprehensive
framework
for
management.
To
improve
predictive
accuracy,
integrates
genetic
algorithms
back-propagation
(BP)
neural
networks,
leveraging
optimize
network’s
parameters
structure.
Additionally,
hierarchical
reinforcement
learning
based
fuzzy
reasoning
(HRL-FR)
proposed
enhance
decision-making
capabilities.
employs
policy
optimization,
incorporating
address
uncertainties
in
complex
dynamic
environments.
Experimental
validation
using
Compustat
dataset
confirms
effectiveness
model.
Key
variables,
working
asset
ratio
debt-to-equity
ratio,
are
identified
as
significant
influencers
reinforcing
model’s
robustness.
The
algorithm’s
search
process
identifies
parameter
combinations
that
maximize
network
performance,
further
improving
Comprehensive
evaluations
conducted
Center
Research
Security
Prices
(CRSP)
datasets
2022
confirm
HRL-FR
superior
ability
predict
analyze
information
accurately.
demonstrates
higher
profitability,
enhanced
efficiency,
curves
closely
align
optimal
models.
These
findings
highlight
potential
powerful
tool
offering
valuable
insights
mitigation
strategic
decision-making.
