Journal of Decision System,
Год журнала:
2024,
Номер
unknown, С. 1 - 27
Опубликована: Окт. 11, 2024
The
current
research
endeavour
aims
to
examine
the
most
recent
advancements
pertaining
AI-powered
ChatGPT
in
scholarly
literature.
Moreover,
this
examines
both
positive
and
negative
aspects
of
utilisation
across
several
sectors
including
business,
research,
society.
data
was
collected
from
Scopus,
using
Preferred
Reporting
Items
for
Systematic
Meta-Analysis
(PRISMA)
methodology.
process
scientific
mapping
carried
out,
wherein
biblometric
thematic
analysis
conducted.
results
suggest
that
there
is
a
significant
amount
being
conducted
on
subject,
particularly
fields
healthcare
education.
Thematic
reveals
wide
range
issues,
examination
impact
technology
decision-making
processes
address
complex
business
challenges.
Theoretical
perspectives
underscore
significance
ethical
deliberations,
regulatory
structures,
interdisciplinary
cooperation,
user
instruction
advancement
implementation
Artificial
Intelligence
systems.
SSRN Electronic Journal,
Год журнала:
2023,
Номер
unknown
Опубликована: Янв. 1, 2023
The
incorporation
of
generative
artificial
intelligence
(AI)
systems,
such
as
ChatGPT,
holds
great
potential
in
reshaping
diverse
facets
architectural
engineering.
This
research
investigates
the
profound
influence
AI
technologies
on
structural
engineering,
HVAC
(Heating,
Ventilation,
and
Air
Conditioning)
electrical
plumbing
fire
protection
sustainability,
net
zero,
green
building
design,
information
modeling
(BIM),
urban
planning,
project
management.
In
ChatGPT's
capacity
to
analyse
extensive
datasets
simulate
intricate
structures
expedites
design
process,
ensuring
integrity
while
optimizing
materials
costs.
it
aids
devising
energy-efficient
systems
climate
control
solutions,
significantly
contributing
sustainable
practices.
Similarly,
AI's
capabilities
enhance
optimization
both
safety
reliability.
ChatGPT
assists
creating
efficient
layouts
suppression
compliance
with
regulations.
Moreover,
plays
a
pivotal
role
advancing
sustainability
design.
By
evaluating
environmental
factors
suggesting
eco-friendly
designs,
fosters
development
environmentally
responsible
structures.
domain
BIM,
facilitates
seamless
collaboration,
automates
model
generation,
improves
clash
detection,
streamlined
execution.
Nevertheless,
integration
engineering
presents
challenges.
Ethical
concerns,
data
security,
necessity
for
skilled
professionals
interpret
AI-generated
insights
are
significant
issues.
delves
into
these
contribution
challenges
effectively
harness
AI,
paving
way
transformative
era
SSRN Electronic Journal,
Год журнала:
2023,
Номер
unknown
Опубликована: Янв. 1, 2023
This
research
paper
delves
into
the
integration
of
advanced
generative
artificial
intelligence
(AI)
models,
such
as
ChatGPT,
Bard,
and
similar
architectures,
within
realms
architectural
design
engineering.
The
comprehensive
study
explores
various
aspects,
including
applications,
frameworks,
challenges,
prospective
developments
in
context
In
domain
design,
investigates
transformative
impact
on
Architectural
Theory,
highlighting
how
AI
fosters
creativity
innovation
thinking.
Design
Process
is
scrutinized,
showcasing
models
streamline
ideation,
iteration,
collaboration
among
teams.
role
Representation
Visualization
explored,
emphasizing
its
capacity
to
generate
immersive
realistic
visualizations.
Furthermore,
examines
influence
Interior
Design,
Urban
Planning,
considers
nuanced
aspects
Cultural
Social
factors,
elucidating
these
technologies
contribute
inclusive
context-sensitive
practices.
Within
realm
engineering,
assesses
Structural
Engineering,
demonstrating
potential
optimize
innovate
structural
analysis
designs
for
enhanced
safety
efficiency.
It
applications
Building
Systems
Construction
Management,
illustrating
can
project
workflows
resource
allocation.
compliance
with
Codes
Regulations
analyzed,
error
reduction
adherence
standards.
Additionally,
probes
Materials
Technology,
advancements
material
selection
construction
methodologies.
also
promoting
Sustainability
Environmental
energy
efficiency,
reduce
environmental
impact,
enhance
overall
sustainability.
While
presenting
critically
evaluates
challenges
posed
by
integrating
domains,
ethical
considerations,
bias
mitigation,
user
adaptability.
Finally,
it
outlines
future
directions
development,
necessity
interdisciplinary
collaboration,
guidelines,
ongoing
fully
harness
shaping
Energy and Built Environment,
Год журнала:
2024,
Номер
unknown
Опубликована: Март 1, 2024
Multiple-chiller
systems
are
widely
adopted
in
large
buildings
due
to
their
high
flexibility
and
efficiency
providing
cooling
capacity.
A
reliable
robust
chiller
sequencing
control
strategy
is
crucial
ensure
the
energy
stability
of
multiple-chiller
systems.
However,
conventional
strategies
usually
based
on
real-time
measured
load
without
considering
changes
following
hours.
Conventional
rule-based
may
result
unnecessary
switching
off,
leading
waste
impairing
system
stability.
Therefore,
this
study
proposes
a
that
utilizes
probabilistic
predictions.
1h-ahead
prediction
form
normal
distribution
made
using
natural
gradient
boosting
(NGBoost).
Compared
machine
learning
algorithms,
NGBoost
can
predict
not
only
future
but
also
uncertainty
predicted
load,
which
enables
handle
uncertainties
associated
with
data/measurements
adequately.
novel
risk-based
developed
The
data
experiment
shows
proposed
significantly
improve
reliability
plant
by
reducing
total
number
up
43.6%.
Energy and Built Environment,
Год журнала:
2024,
Номер
unknown
Опубликована: Март 1, 2024
Large
language
models
(LLMs)
have
shown
human-level
capabilities
in
solving
various
complex
tasks.
However,
it
is
still
unknown
whether
state-of-the-art
LLMs
master
sufficient
knowledge
related
to
heating,
ventilation
and
air
conditioning
(HVAC)
systems.
It
will
be
inspiring
if
can
think
learn
like
professionals
the
HVAC
industry.
Hence,
this
study
investigates
performance
of
on
mastering
skills
industry
by
letting
them
take
ASHRAE
Certified
Designer
examination,
an
authoritative
examination
Three
key
are
explored:
recall,
analysis
application.
Twelve
representative
tested
such
as
GPT-3.5,
GPT-4
LLaMA.
According
results,
passes
with
scores
from
74
78,
which
higher
than
about
half
human
examinees.
Besides,
GPT-3.5
twice
out
five
times.
demonstrates
that
some
great
potential
assist
or
replace
humans
designing
operating
they
make
mistakes
sometimes
due
lack
knowledge,
poor
reasoning
unsatisfactory
equation
calculation
abilities.
Accordingly,
four
future
research
directions
proposed
reveal
how
utilize
improve
industry:
teaching
use
design
tools
software
industry,
enabling
read
analyze
operational
data
systems,
developing
tailored
corpuses
for
assessing
real-world
operation
scenarios.
