Journal of intelligence and knowledge engineering.,
Год журнала:
2024,
Номер
2(1), С. 37 - None
Опубликована: Март 1, 2024
Climate
change
has
caused
an
increasing
threat
of
flood
disasters,
and
using
artificial
intelligence
methods
to
predict
floods
is
now
a
hot
subject
in
the
field
prediction.
To
find
out
current
situation
prediction
research
based
on
methods,
it
essential
summarise
main
focus
direction
at
present.
612
references
forecasting
AI
were
selected
from
Web
Science
Core
Collection
database.
The
collected
articles
analysed
visually
CiteSpace
VOSviewer.
results
study
indicate
that
overall
trend
publications
AI-based
studies
increasing.
In
particular,
China,
United
States
India
are
contributors
this
area.
analysis
collaborating
institutions
shows
Chinese
have
high
activity
field.
keywords
term
show
mainly
focuses
three
aspects,
which
risk
assessment,
hydrological
information
simulation,
integration
improvement
algorithms.
recent
years,
(AI)
algorithms
became
as
new
focal
point
research.
incorporation
multiple
machine
learning
or
deep
well
additional
improve
quality
models
received
attention
future,
important
for
efforts
explore
these
avenues
further,
order
strengthen
China's
scientific
efficient
response
capabilities
face
disasters.
This
study's
can
be
reference
researchers
understand
landscape
emerging
frontiers
AI-driven
It
will
help
guide
future
directions
strategies
promote
continued
development
Expert Systems with Applications,
Год журнала:
2023,
Номер
236, С. 121426 - 121426
Опубликована: Сен. 4, 2023
Cutting-edge
flood
visualisation
technologies
are
becoming
increasingly
important
in
managing
urban
risks,
particularly
from
the
perspective
of
stakeholders
who
play
a
crucial
role
controlling
and
reducing
risks
associated
with
events.
This
review
study
provides
comprehensive
overview
stakeholder
analysis
this
context,
highlighting
gaps
current
research
paving
way
for
future
investigations.
For
purpose,
scientific
literature
critical
conducted
based
on
identified
relevant
works
to
map
mutual
context.
categorises
cutting-edge
into
four
groups
-
virtual
reality,
augmented
mixed
digital
twin
explores
their
adoption
engaging
various
across
five
key
stages
risk
management:
prevention,
mitigation,
preparation,
response,
recovery.
Results
show
that
existing
has
primarily
concentrated
support
water
utilities
communication
general
public.
However,
there
is
noticeable
gap
regarding
engagement
such
as
policy-makers,
researchers,
insurance
providers.
Furthermore,
highlights
disparities
involvement
damage
assessment
studies,
lack
representation
policy-makers
researchers.
Finally,
introduces
concept
overlooked
interconnected
impacts
they
have,
which
received
relatively
little
attention
previous
research.